We invite committed and enthusiastic individuals to join the Centre for Independent Living in Toronto’s (CILT) dynamic Board of Directors as we continue to empower people with disabilities to live independently and take control of their own lives.

• Support CILT’s operations and the hundreds of consumers we serve across a variety of programs geared toward opportunities for people with disabilities to learn skills necessary for successful inclusion into society, including social and economic opportunities.
• Have a say in the direction of the organization and ensure we are on track to meet the goals set by the strategic plan
• Make a meaningful difference in the lives of people with disabilities and help shape a more inclusive community
• Gain experience contributing with a diverse and dynamic CILT Board of Directors and establish professional connections

• Understands, supports and is committed to the Independent Living philosophy
• Familiar with the disability community in Toronto and the surrounding area
• Experience developing/delivering budgets and financial statements is an asset

• CILT’s Board of Directors meets approximately every 2 months for 1.5-2 hours
• Meetings take place virtually over Zoom. Directors are also welcome to join by phone

• Directors are responsible to Members of the organization. The Director acts as a trustee on behalf of all members of CILT and people with disabilities in Toronto and the surrounding area.
• Directors are expected to attend all board meetings, including the Annual General Meeting (AGM), and arrive on time. Meeting minutes and documents are provided prior to the meetings and should be reviewed in advance.
• Directors understand and oversee all CILT’s finances. They must participate in the decision-making process by expressing insights, thoughts, opinions, and concerns related to CILT, and when appropriate, volunteer to serve on Board sub-committees. Any potential conflicts of interest must be declared, and all matters of the organization must be treated with confidentiality and sensitivity.
• Accept all other duties as required and adhere to the organizational By-laws and policies.

If you are interested in applying to join CILT’s Board of Directors, please submit your resume and cover letter to cilt@cilt.ca by September 4, 2026. All applications will be reviewed by the Nominations Committee of the CILT Board of Directors.

We encourage applications from disabled people who are also Black, Indigenous, People of Colour, 2-Spirit, LGBTQ+, Immigrants and Refugees, people living in poverty, unhoused, under-housed people and anyone else from communities experiencing systemic barriers.

The Centre for Independent Living in Toronto (CILT) is a consumer-controlled, community-based resource organization dedicated to supporting people with disabilities to live independently and participate fully in their communities. Grounded in the principles of the Independent Living (IL) movement, CILT is “for persons with a disability… by persons with a disability.” A majority of CILT’s board and staff are people with disabilities, ensuring that the organization remains consumer-directed and reflective of lived experience.

CILT’s By-laws require that the majority of the board shall be made up of disabled consumers and that the positions of President and Vice-President shall at all times be a disabled consumer.

For more information about CILT, please visit www.cilt.ca 

The post CILT appeared first on Capacity Canada.

Position: Board Member (Volunteer, 4 positions available)
Deadline: September 15, 2026
Organization: Necessary Angel Theatre Company
Website: necessaryangel.com

Founded in 1978, Necessary Angel pioneered idea-based artist-driven theatre creation processes, influencing a generation of English-speaking companies and artists. The company has always taken a multi-year approach to development, exploring complex contemporary themes, in unique sites and with boundary-pushing scopes. Many of our projects have been widely acclaimed and toured. NA has been awarded the Governor General’s Awards for Drama, Chalmers Awards for Outstanding New Play and numerous Dora Mavor Moore Awards. The company was awarded the Lieutenant Governor’s Award for the Arts in 1998.

Necessary Angel has created over 60 productions, including over 30 world premieres and 11 North American premieres. To support these projects, Necessary Angel pioneers an artist-led, exceptionally open-ended development process. We have been privileged to work with outstanding literary figures such as Michael Ondaatje and Timothy Findley. A catalyst for groundbreaking original work, Necessary Angel has collaborated with some of Canada’s most acclaimed theatre artists: Jordan Tannahill, Dairine Ni Mheadra, Daniel MacIvor, Saidah Baba Talibah, John Mighton, Colleen Murphy, Teresa Przybylski, Jason Sherman, Colleen Wagner, David Young, Marie-Josee Chartier and Jonathon Young.

Richard Rose was Necessary Angel’s founder and Artistic Director from 1978 to 2008, Daniel Brooks from 2008 to 2012, and Jennifer Tarver from 2013 to 2018. Alan Dilworth was appointed as Necessary Angel’s fourth Artistic Director in June 2019.

Necessary Angel Theatre Company has always supported artistic voices, process, and innovation over institutional growth.

As of 2020, Necessary Angel has implemented a series of Artist Residencies that have centered Indigenous artists, artists of colour, new generation artists, and artists outside of Toronto. These residences are part of the NA LAB and have been central to our artistic programming both on the stage and off, and are at the heart of our vision of radical connection.

For nearly 50 years, Necessary Angel Theatre Company has been one of Canada’s leading creators of original theatre, producing bold, innovative, and socially relevant work.

Necessary Angel Theatre Company is seeking four new members to join its Board of Directors, with new terms beginning November 2026. As a volunteer board member, you will play an important role in the

governance, strategic direction, and long-term sustainability of Necessary Angel. Our highly professional and diverse board brings together leaders from a wide range of industries, offering an exceptional opportunity to build meaningful relationships while helping shape the future of one of Toronto’s and Canada’s leading independent theatre companies.

• Provide strategic oversight and contribute to the governance and growth of Necessary Angel
• Serve as an ambassador for the organization and help expand awareness of Necessary Angel’s mission and impact
• Serve as an active member of at least one board committee: Finance, Fundraising, or Governance
• Use your personal and professional network to identify and introduce prospective donors, sponsors, corporate partners, and community supporters
• Support donor cultivation, stewardship, and fundraising initiatives through relationship-building, outreach, and strategic introductions
• Collaborate with the Board of Directors and Artistic Director to advance organizational priorities and strengthen long-term financial sustainability
• Attend Board meetings and participate in Board discussions and initiatives. (Board meetings are held 5-6 times a year and are generally 90 minutes in length, via Zoom or in person.)
• Support Necessary Angel productions, events, and community engagement activities when possible

Necessary Angel is seeking board members who have a passion for the arts and a commitment to Necessary Angel’s mission, who have excellent communication and interpersonal skills, and who are strategic thinkers with a collaborative approach to leadership. Applicants with previous board or committee experience is an asset.

Necessary Angel strongly encourages applications from Indigenous, Black, racialized candidates, persons with disabilities, persons of all gender identities, artists, newcomers, members of the 2SLGBTQI+ communities and those identifying with other equity-deserving groups.

We are recruiting across three priority areas — candidates need not have experience in all three: Arts & Cultural Sector, Business & Finance, and Fundraising & Philanthropy.

Preferred qualifications and experience by priority area:

• Passion for arts and culture
• Familiarity with the non-profit cultural landscape and artist communities in Toronto and Ontario
• Working theatre artists, and young/emerging theatre artists

• Background in finance, or professional experience within a corporate environment or financial institution
• Financial literacy, with skills to read/analyze financial statements and manage budgets and with a willingness to join the board’s Finance Committee

• Experience in fundraising, philanthropy, donor cultivation, capital campaigns, or major gifts
• An established network of philanthropic, corporate, or community connections, with the ability and willingness to connect Necessary Angel with prospective donors, sponsors, and partners
• Comfort engaging in donor conversations, making introductions, and supporting fundraising initiatives

Please submit the following to info@necessaryangel.com with subject line ‘Board Member Application’ by September 15, 2026:

• A cover letter including a brief statement of interest (one page or less) describing your relevant experience and why you’d like to join the Necessary Angel Board of Directors
• A current resume or biography

Shortlisted candidates will be invited to a conversation with the Governance Committee in September 2026

• New members will be confirmed by the Board and welcomed onto the board in November 2026.

Necessary Angel Theatre Company is committed to equity, diversity, and inclusion and accessibility, and strongly encourages applications from Indigenous, Black, and racialized candidates, artists, newcomers, persons with disabilities, and members of the 2SLGBTQIA+ communities and persons who identify with other equity-deserving groups.

The post Necessary Angel Theatre Company appeared first on Capacity Canada.

♦“They Help Everybody!”

In 2019, Zineb and her family arrived in Canada after spending 10 years in the United States.

They had left Libya in 2008, so Zineb’s husband could study for a PhD in Chemistry, on a scholarship. When his studies ended, they could no longer stay in the U.S.

They decided to move to Canada. They wanted to give their children a chance to study here, seeing more opportunities than they had in the States.

While in the U.S, the family lived in university housing and had some money, but not a lot. Most of the social support available in the United States was restricted to U.S. citizens. Zineb’s family couldn’t access basic supports like food stamps.

And because they were there on a student visa, they couldn’t legally work in the United States, making it very difficult to make ends meet.

When they moved to Canada, a friend helped them find a house to rent in Waterloo, but it had no furniture. With very little money left after the move, they found bedding at Value Village so they could sleep on the floor. 

“We had nothing when we got here,” said Zineb. “We only had clothing.”

That Saturday, Zineb was walking near her home and met a neighbour.

“She showed me the Sunnydale community centre,” said Zineb. “I came on Monday and met Marwa and Fariba. I told them, ‘I am a newcomer here. And they helped me.’”

Marwa, a Community Development Worker at House of Friendship, spoke to Zineb in Arabic, helping her feel more at home. And Fariba, a Family Outreach Worker, sat down with her to help Zineb find the support she needed.

Fariba quickly helped Zineb get some furniture.

“I received beds for everybody, and a sofa, and a table, and stuff for the kitchen,” said Zineb. “I was crying.”

Since then, Zineb found part-time work as a lunchroom supervisor. Unfortunately, her husband has been unable to find work, despite his extensive education. Zineb has encouraged her children to be practical with their education, finding programs that will lead to good jobs.

Zineb has also made Sunnydale Community Centre a second home, going there for the support she needs, as well as regularly volunteering with the food program.

 “This area has many programs for families and children,” said Zineb. “House of Friendship is very good. I tell my friends, ‘The community centre will help you – they help everybody!’”

The post They Help Everybody appeared first on House Of Friendship.

Look it's one thing to be a cheerleader versus a watchdog but at some point you have to insist that Lanxess comply with their Control Orders, Environmental Compliance Agreements, MISA requirements and other mandated conditions affecting Elmira's groundwater cleanup as well as the cleanup of the Canagagigue Creek. Yesterday we discussed their failure to maintain the balance between on and off-site pumping necessary to ensure hydraulic containment in both areas. 

Again I have the data going back to 1997 at my fingertips showing the volume of pumping from the UACS (Upper Aquifer Containment & Treatment System). Each month I transfer the pumping results from the ongoing Progress Reports onto one individual page for the year thus reducing 12 monthly reports pumping information for all containment systems to a single page. Now if Lanxess Canada had made some sort of breakthrough several years ago that magically reduced the required amount of pumping and treating of groundwater, they certainly haven't publicly made a big deal of it. In fact for many years the Target pumping rates for each well along with the actual pumping that particular month were discussed in detail. Uniroyal, Crompton and Chemtura were occasionally balancing and adjusting based upon water level conditions ("Gig") and other factors which they openly and properly discussed with the UPAC and CPAC committees. We were often advised that short term reductions were not necessarily a problem however the Target pumping rates were carefully set in order to maintain the necessary hydraulic containment and avoid loss of contaminants from on-site either to off-site groundwater or for the leakage of contaminants from the on-site Upper Aquifer to the discharge point into the Canagagigue Creek.     

Above and beyond the committee members themselves is the fact that all actions and particularly changes from past practices are to be discussed at the public RAC/TAG and now TRAC meetings. When pump & treat is the primary remediation method it is of particular public interest to discuss rationales for any changes in pumping regimens, especially reductions. This has not been done either for on-site Municipal Upper Aquifer (MU) pumping or for on-site shallow groundwater (i.e. Upper Aquifer-UA) pumping. The pumping rates have simply been getting lower and lower over the last several years with no public discussion involved. Whether or not I have been able to stomach in person attendance at these alleged public meetings the fact is that I have watched and listened to them in their entirety via their on-line presence. I have also written critiques of each and every one afterwards. Perhaps there are implications to these Lanxess Canada, MECP and TRAC UA pumping failures somewhat similar to the implications I wrote about yesterday concerning the Municipal Upper Aquifer (MU) pumping failures.

♦

Coffee shops are everywhere, the good and the merely mediocre — McDonald’s coffee, among the latter, is still much, much better than Tim Hortons’, I have to say.

The most heartening aspect of the phenomenon is that the vast majority of local coffee shops are independents, each possessed of its own character and quality in a sea of java sameness. That means choice for consumers over and above the national chains.

This growth in a food culture when it comes to coffee continues a long tradition of the beverage as a popular recreational drug-of-choice, from accounts of Ethiopian goatherds chewing coffee as early as the 9th century to records of coffee being roasted and sipped by the 1550s.

London, England, for instance, got its first coffeehouse in 1652 and by the 18th century coffeehouses were firmly entrenched as hot houses for literary badinage and repartee about the latest fashion and gossip, and desultory kvetching about politics though some of that would have birthed its share of successfully hatched schemes, plots and subterfuges.

An added layer of shenanigans that took place at coffeehouses and chocolate houses—the latter having appeared as the perfect partner to the beverage in London by 1657—was gambling: at the Cocoa-tree Club in London in 1770, Lord Stavordale lost thousands of pounds in a card game.

Elsewhere, at Don Saltero’s Tavern in Chelsea (established in 1695, pictured above), you could have enjoyed a haircut and gotten some dental work done too.

Now, I haven’t seen any high stakes card games in area coffeehouses—nor have I seen periodontal work or prophylaxis being performed—but I have enjoyed a wide range of varying coffee cultures.

It is its cultural component that most interests me: coffee is a supremely contemplative drink conducive to conversation and social interaction, unlike any other foodservice sector perhaps.

Each shop in Kitchener and throughout Waterloo Region, for that matter, has something different to offer. There are a couple characterized by a faintly bohemian feel with couches, suffused light, vegan fare and an uber-laidback vibe. Some provide live entertainment, board games and small libraries with reading room-style seating.

As for fair trade and organic, it’s the right thing to do. There are many coffee aficionados and just casual sippers looking for responsible, sustainable brews and several outlets offering it. Coffee is a damn hard commodity to grow and farmers on the ground in coffee-growing regions too often take it on the chin.

Still other venues roast their own beans and are students of an artisan philosophy that moves beyond the coffea arabica and coffea robusta bean basics to a wide-world of esoteric coffees and the heady realm of the barista, the coffee expert who plies his or her trade from behind a glittering Italian espresso macchina worth as much as the addition I put on my house.

And while I enjoy the odd latte, espresso and cappuccino (and not because it sounds somewhat like my last name), I draw the line at the overly enthusiastic multi-syllabic orders—nonfat-mocha-frappa-misto-ventes—that take 10 seconds to blurt out. There are many of those around if that’s the exhilarating juice you desire, but I stick with Juan Valdez’s best flavours as simple and strong as I can get them, unadorned by sweeteners and cream.

The food in coffeehouses is of little concern for the die-hard java hound in search of a hot dose of the devil’s cup. There are sweets and savouries here and there—a biscotti, a muffin, a croissant—but the real, the traditional, draw is the cup of joe, the fix, the black liquid lightning.

Yet, all of this is a brew for a percolating discussion. Local coffeehouses jazz up a region’s food culture with a jolt of energy balanced with a relaxed atmosphere that’s perfect for casual conversation and friendly argument.

And maybe the odd kvetch about politicians.

banner image/By Bodleian Library, University of Oxford – Bodleian Library, University of Oxford, Public Domain, commons.wikimedia.org/w/index.php?curid=8343739

Check out my latest post Coffee culture is robust — and ancient from AndrewCoppolino.com.

Over the last few years, I have helped put together several engineering teams across very different environments.

And somewhere along the way, I became much less interested in the question:

“Who is the strongest engineer?”

Because the strongest engineer on paper was not always the person who made the team stronger.

Sometimes the person who looked exceptional individually created more friction than value around them. Sometimes the quieter engineer became the reason five other people could move faster. Sometimes the obvious senior hire added more of a capability we already had, while the person we actually needed looked less impressive on a traditional scorecard.

After enough teams, a pattern started to become clear:

Engineering talent is not really a ranking problem. It is a composition problem.

Because a team of strong individuals is not automatically a strong team.

Imagine two engineers.

Max ships features incredibly fast. His output is obvious, measurable, and easy to reward.

Sara ships less herself, but somehow six other engineers move faster when she is around. She decomposes problems clearly. She notices dependencies before they become incidents. Product conversations become less ambiguous. Junior engineers become more independent. Architecture discussions eventually become decisions.

If you measure individual productivity, Max probably wins.

If you measure how quickly the whole organization can move, Sara becomes much harder to ignore.

That distinction is becoming increasingly relevant. McKinsey’s 2026 Global Tech Agenda describes a move toward capability-led talent models and greater focus on organizational velocity rather than simply adding capacity. The useful part of that framing, for me, is that it changes the unit of thinking.

Instead of asking:

How many engineers do we need?

You start asking:

What does this team actually need to be able to do?

And those are very different questions.

A team modernizing a legacy platform may need someone who understands all the ugly historical decisions buried inside it. It may also need someone who can design what replaces it without turning the project into a three-year architecture exercise. Someone else may be excellent at moving from ambiguity to working software. Another person may be unusually good at connecting product, business, and engineering.

None of them has to be “the best engineer.”

Together, they may be exactly the team you need.

This is where engineering leadership starts looking suspiciously like architecture.

When we design technical systems, we think in terms of capabilities, dependencies, bottlenecks, redundancy, and failure modes. We do not ask which component is the most impressive.

Yet we often forget to use the same thinking with teams.

Consider the engineer who knows everything.

Every strange production issue ends up with them. They know why an ancient database table still exists. They know which service cannot be restarted at 4 PM. When something breaks, somebody says, “Ask Alex.”

Alex looks indispensable.

And Alex probably is.

But if the system cannot safely operate without Alex, you have also created a human single point of failure.

If this were software architecture, we would identify the dependency and try to remove it. When the dependency is a person, we sometimes reward it instead.

That does not mean making Alex less valuable. It means turning Alex’s knowledge into organizational capability: shared ownership, documentation, pairing, simpler systems, better operational practices.

The same thinking changes hiring.

“We need another senior engineer” is not a particularly useful requirement.

Do you need more delivery capacity?

Deep domain knowledge?

Someone who can simplify an overengineered platform?

Someone who can work across product and technology?

Someone who can make less experienced engineers stronger?

The most impressive candidate may still be the wrong hire if they add a capability you already have five times over.

It changes promotion decisions too.

Promotions do not just reward people. They teach the organization what is valuable.

If the person repeatedly saving production at midnight gets promoted while the person quietly preventing incidents does not, people notice.

If complex architecture gets more recognition than simplification, people notice that too.

If individual heroics consistently beat mentoring and knowledge sharing, you should not be surprised when your organization produces more heroes and more dependencies.

People are extremely good at discovering what a company actually rewards.

Usually better than they are at remembering what is written in its values deck.

This is also why some contributions are so easy to underestimate.

An engineer who can move fluently from business problem to product decision to architecture to implementation may not be the strongest person in any single category.

Their advantage is the combination.

They connect layers that organizations often separate. They catch misunderstandings earlier. They help teams build the right thing before everybody gets very efficient at building the wrong thing.

That kind of value is difficult to see if the main question is still, “Who produces the most?”

Engineering leadership, then, is less about ranking talent and more about composing it.

Not in the sense of turning people into boxes on an architecture diagram. People are fortunately much less predictable than microservices.

But the questions are surprisingly similar.

• Where does critical knowledge live?
• Which capabilities are missing?
• Where do we have unnecessary duplication?
• Who makes the people around them better?
• Where have we created dependencies that would hurt if someone left?
• What does this particular team need now that it did not need a year ago?

That last part matters.

The right composition changes.

A startup trying to prove an idea needs something different from a platform team operating at scale. A modernization program needs something different from a greenfield product. A team in crisis needs something different from a team that has become too comfortable.

So perhaps “Who is the strongest engineer?” was never the most useful leadership question.

Sometimes you already have several exceptional engineers. What your team desperately needs is something else.

There is also one uncomfortable question this way of thinking creates:

How do you know you are actually composing a better team, rather than just rationalizing the team you already have?

Because “we need different kinds of strengths” can become a convenient excuse for avoiding harder performance decisions.

Composition is not a softer alternative to talent quality.

There still has to be a bar.

People still need to execute.

They still need clear ownership.

They still need to be accountable for outcomes.

And not every dependency is automatically bad either. Sometimes, especially in smaller or fast-moving teams, concentrating knowledge in one person is the fastest way to move. The real question is whether that dependency is intentional, temporary, and understood.

The same applies to redundancy. Sharing knowledge is useful. Duplicating every capability everywhere is not.

So maybe the real leadership questions are harder than simply asking who the strongest engineer is.

What capability is actually constraining the business right now?

Is this person a force multiplier, or have we just found a sophisticated way to avoid measuring their individual contribution?

Would I design this team the same way if I were starting from zero today?

For me, that is where the idea of composition becomes useful.

Not as an argument against individual excellence.

Not as an argument for keeping everyone.

And certainly not as a reason to make engineering teams into perfectly balanced collections of personality types.

The composition is only good if it helps the company do something better: move faster, make better decisions, build more reliable systems, learn more quickly, or create capabilities it did not have before.

So I still would not ask, “Who is the best engineer?”

I would ask:

What is the business trying to become capable of next — and do we have the right people, in the right combination, to get there?

Maybe that is the question I have come to trust more.

Engineering Talent Is a Composition Problem was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Why would they do that? Money obviously is the most likely culprit. Have they figured out that if they can't reach the 2028 Elmira groundwater cleanup deadline then they may as well cut back on pumping and treating in order to save themselves money? But wait a minute! Their off-site (i.e. beneath Elmira vs. beneath their site)  pumping figures don't reflect that. In fact they are pumping as much or more off-site than they've ever pumped. Ahh! The dirty, slimy, rotten so and so's! Notice here that I have not named Hadley, Lou, Jason or Lubna or anybody else from Lanxess/GHD/MECP as specifically being the "...dirty, slimy, rotten so and so's."  That could be construed as either rude or disrespectful and heaven forbid I'd never want anybody to suspect that I have zero respect for professional liars, especially those on the taxpayers' payroll, who would dissemble or deceive their true employers.

So what are the poor, misguided, obviously soul and ethics damaged folks at Lanxess doing? Well simply by looking backwards, something I challenge TRAC to do now and then, one can learn the answer. Since 2019 Lanxess, right in front of the Ontario Ministry of Environment (MECP), are significantly cutting back on their on-site Municipal Upper Aquifer pumping. Now keep in mind they've already achieved permission not to have to maintain 100% hydraulic containment on their site as they were originally ordered to do. The sad theory is that contaminants that escape from their north-west property boundary allegedly are recaptured by either on-site PW4 or off-site W5 A/B. This scheme supported by CPAC, APTE and the MECP at the time appears not to worry that they (Uniroyal/Crompton) have increased contamination for private property owners along the west side of their industrial site. This concession saved the company money just as their unilateral/bilateral decision starting in 2019 to cut back on pumping the most heavily contaminated and hence most expensive pump & treat on-site area did so. 

Way back in time, before RAC/TAG & later TRAC came along, one Jeff Merriman from Chemtura promised CPAC that on-site pumping (PW4 & PW5 at the time)  would average 6.0 litres per second in order to assure full on-site hydraulic containment. Averages probably for a while were closer to 5.8 or 5.9  litres/sec but they were at least close. Then under Lanxess Canada they started to fall and continued to do so. Now certain honest, albeit softly misguided individuals currently on TRAC such as Sebastian do not have the full past pumping  regimens of all pumping wells at their fingertips as I do. Most certainly neither does Susan Bryant who does not share Sebastian's attributes of honesty and being only softly misguided. Hence TRAC mostly composed of citizen members with less than five years experience  have simply ignored both on and off site pumping rates because they have nothing to compare them to despite 34 1/2 years of on-site pumping and more than 28 years of off-site pumping. All the data are in the monthly Progress Reports although that's too onerous for volunteers to dig through as I have.

So in the short term Lanxess cut back on their most expensive pumping and treatment costs AND guess what? By pumping less on-site and more off-site they are intentionally losing on-site hydraulic containment. This means that they are purposefully drawing contaminants off their site where they Lanxess only pay 50% of those cleanup costs versus 100% of all on-site treatment costs. We the taxpayers pay the other 50% of the off-site costs. This of course also lengthens and stretches out  the time needed to fully and properly remediate the (off-site) Elmira Aquifers.

I call this at the least gamesmanship and at the worst fraud. Certainly it also shows gross disrespect of Elmira citizens and all citizen taxpayers. Not a peep out of RAC/TAG or TRAC because mayor Sandy Shantz intentionally eliminated those of us on CPAC in late 2015 with the knowledge and honesty to oppose this deception and gamesmanship.   

The Waterloo Region real estate market slowed noticeably in July compared with June, with fewer home sales, softer prices and longer selling times. At the same time, fewer new listings came to market and overall housing inventory also declined.

The market remains active, but increasingly selective. Buyers are paying close attention to value, and the way a home is prepared, priced and positioned continues to have a significant impact on the results sellers are achieving across Kitchener, Waterloo and the surrounding communities.

Compared with June 2026 and July 2025:

• 579 homes sold — ↓ 10.9% vs. June | ↓ 10.4% year-over-year
• $707,016 average sale price — ↓ 3.2% vs. June | ↓ 3.8% year-over-year
• $675,000 median sale price — ↓ 2.2% vs. June | ↓ 2.9% year-over-year
• 1,158 new listings — ↓ 17.3% vs. June | ↓ 14.5% year-over-year
• 1,927 homes for sale — ↓ 6.1% vs. June | ↓ 9.4% year-over-year
• 33 days on market — up from 27 days in June and 32 days in July 2025
• 3.9 months of inventory — down from 4.1 in June and 4.0 last July
• 100.2% of the most recent list price received — down from 100.9% in both June and July 2025
  
  

Cornerstone Association of REALTORS®

Year-to-date, residential home sales in Waterloo Region are 5.9% lower than 2025, while the average sale price is down 4.8% and the median sale price is down 5.0%.

While the headline numbers point to softer conditions overall, there continues to be a meaningful difference between the performance of single-family homes and the townhouse, semi-detached and condominium market.

Single-family homes continued to demonstrate stronger relative demand in July.

• 383 sales — ↓ 10.9% vs. June | ↓ 1.0% year-over-year
• $811,734 average sale price — ↓ 3.2% vs. June | ↓ 5.2% year-over-year
• $760,000 median sale price — ↓ 1.9% vs. June | ↓ 3.4% year-over-year
• 30 days on market — up from 23 in June and 28 last July
• 3.2 months of inventory — down from 3.4 in June and 3.4 last July
• 100.3% of the most recent list price received

Cornerstone Association of REALTORS®

Year-to-date, single-family home sales are actually slightly ahead of 2025, increasing by 0.4%.

With fewer months of inventory and considerably stronger year-over-year sales activity than the townhouse and condominium segment, detached and other single-family homes continue to be the more resilient part of the Waterloo Region housing market.

That does not mean every home is selling quickly. Days on market increased substantially from June, and buyers remain highly sensitive to price. Homes that are well positioned relative to their competition are generally seeing a much stronger response than properties that enter the market above where buyers perceive their value to be.

The townhouse, semi-detached and condominium segment continues to offer buyers more choice and greater negotiating power.

• 196 sales — ↓ 10.9% vs. June | ↓ 24.3% year-over-year
• $502,390 average sale price — ↓ 3.4% vs. June | ↓ 9.5% year-over-year
• $516,500 median sale price — ↓ 1.6% vs. June | ↓ 10.5% year-over-year
• 39 days on market — up from 35 in June and unchanged from last July
• 5.1 months of inventory — down from 5.4 in June and unchanged year-over-year
• 99.9% of the most recent list price received

Cornerstone Association of REALTORS®

Year-to-date, sales in this segment are down 15.6% from 2025, while both the average and median sale prices have declined 8.3%.

With more inventory and longer selling timelines than the single-family segment, this part of the market remains particularly price sensitive. Buyers have more comparable properties to choose from, which makes accurate pricing, strong presentation and a well-planned launch especially important for sellers.

Homes are selling, but the margin for error on pricing has become very small.

Determining an accurate market value in the current environment can require significant analysis. In some cases, we spend hours evaluating a property before arriving at the pricing strategy we believe gives the seller the strongest opportunity for a successful sale.

There is far more involved than pulling a handful of recent comparable sales and averaging the numbers.

When pricing a home in Kitchener-Waterloo and throughout Waterloo Region, we consider factors such as:

• Recent comparable sales
• Current competing listings
• Neighbourhood and specific location
• Lot size and characteristics
• Finished square footage
• Condition and age of the home
• Quality and extent of renovations
• Floor plan and functionality
• Number of bedrooms and bathrooms
• Finished basement space
• Current buyer demand
• Available inventory
• Days on market
• Previous pricing and listing history

When there are not enough truly comparable recent sales, the analysis becomes more involved. We may need to look back several years, review historical market trends and adjust previous sale prices to understand what a similar property would reasonably be worth in today’s market.

Every meaningful difference has to be considered. A larger lot, superior location, additional bedroom, finished basement, quality renovation or more functional floor plan can all materially affect value. Even two homes that appear very similar on paper can attract different buyers and ultimately achieve very different results.

Market data is important, but so is understanding the context behind it.

An agent who has worked through different real estate cycles has seen how buyer behaviour changes when inventory is low, when supply increases, when prices are rising rapidly and when values begin to correct.

That experience can help determine which comparable sales are genuinely relevant and which may look similar at first glance but provide very little useful information about the property being priced.

Ultimately, the numbers need to support the recommendation.

When the analysis is thorough and the home is positioned correctly, we are still seeing buyers respond quickly and, in some cases, compete. When a property misses the market on price, even by what may appear to be a relatively small amount, the difference in showing activity and buyer interest can be significant.

That is why the strongest results tend to come when pricing, preparation and marketing are treated as one coordinated strategy from the beginning.

Sellers also need to be strategic about where they spend money before listing.

Not every home requires extensive renovations or a significant investment to sell successfully. In many cases, part of our job is helping sellers determine what not to spend money on, which improvements buyers are most likely to value and where time and money can have the greatest impact.

Depending on the property, the right preparation may involve staging, decluttering, minor repairs, paint or targeted cosmetic improvements rather than a major renovation.

The goal is not to make every home perfect. It is to make informed decisions that help the property show at its best, appeal to the right buyers and support the overall pricing strategy.

CMHC’s Summer 2026 Housing Market Outlook points toward a gradual recovery rather than a sudden rebound.

For Kitchener-Cambridge-Waterloo, CMHC is forecasting approximately 6,100 MLS® sales in 2026, essentially unchanged from 6,115 sales in 2025.
The average sale price is forecast to decline to approximately $730,000 in 2026, compared with $754,842 in 2025, reflecting the continued pressure on home prices we have been seeing locally.

Looking further ahead, CMHC expects market activity to gradually strengthen:

• 2027: approximately 6,900 MLS® sales and a $740,000 average sale price
• 2028: approximately 7,450 MLS® sales and a $780,000 average sale price

Overall, the forecast is consistent with the conditions we are seeing throughout Waterloo Region. The housing market is expected to remain relatively subdued through 2026, followed by a gradual improvement in sales activity and pricing through 2027 and 2028.

There are still active buyers in the Waterloo Region real estate market, but this is not an environment where sellers can afford to guess on price or strategy.

The strongest outcomes are generally occurring when the market analysis is thorough, the home is properly prepared and the pricing and launch strategy are aligned from the outset.

The significant difference between property types also means there is no single strategy that works for every home. A detached home in a low-inventory neighbourhood may require a very different approach than a condominium competing against several similar units.

For homeowners considering selling, understanding the market for your specific property, neighbourhood and price range is far more useful than relying on Waterloo Region averages alone.

For buyers, current conditions provide more choice, more time to assess value and, in many cases, greater negotiating opportunity than during the highly competitive markets of recent years.

That can create opportunities, particularly within market segments where inventory remains elevated. However, well-priced homes in desirable locations can still attract significant interest, so buyers should not assume that every property will be heavily negotiable simply because overall market conditions have softened.

The July 2026 Waterloo Region real estate market continued to shift toward more balanced and price-sensitive conditions. Sales and home prices declined from June, properties took longer to sell and buyers remained selective.

At the same time, inventory also declined, and the market continues to vary significantly by housing type, neighbourhood and price point.

For sellers, accurate pricing, thoughtful preparation and a coordinated marketing strategy remain critical. For buyers, increased choice and longer selling timelines are creating more opportunities to carefully assess properties and negotiate where market conditions allow.

If you are considering buying or selling a home in Kitchener, Waterloo or the surrounding Waterloo Region communities, downsizing, relocating or simply want a detailed assessment of what your home may be worth in today’s market, The Deutschmann Team would be happy to help.

Our recommendations are based on the property itself, the competition it is facing and what buyers are actually doing in the current market.

The post Waterloo Region Real Estate Market Update | August 2026 appeared first on Kitchener Waterloo Real Estate Agent - The Deutschmann Team.

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We are seeing some nice plump Ontario raspberries, or will be very soon. More than even fresh local strawberies, I favour raspberries.

The delicate and easily bruised tender fruit has a relatively short season in Ontario from now until September or October, but they always deliver huge flavour and berry satisfaction.

Botanically a member of the rose family, raspberries are part of a group of berries known as “caneberries,” which grow on thin and thorny stalks or “canes.”

They likely originated in Asia thousands of years ago and eventually made it to the west in the 1600s where they have been cultivated ever since. They thrive in temperate northern regions of the world.

The caneberry group includes blackberries, loganberries, boysenberries and cloudberries, which are found in Scandinavia. You might also see them in deep purple or golden hues.

Because they are not a single fruit derived from the plant’s ovary, like a blueberry, raspberries are not considered a true berry.

And whatever colour, they are delicious however perishable and fragile they might be. While they can be picked mature but still green, they will ripen quickly and usually have a relatively short shelf-life of only a few days even in the refrigerator. They are difficult to wash as well.

Despite their delicate nature, raspberries are versatile. While they are probably best consumed as a fresh fruit and eaten on their own for peak flavour (I particularly like them on my breakfast cereal), they also make interesting sauces for beef, pork, duck and even scallops.

To do that, combine raspberries with an acid such as cider, red wine, balsamic vinegar, or some sherry, along with a bit of sugar and cook the combination to reduce it.

As such, raspberries can contribute a delightful sweet-and-sour component to a main course protein or be used in a salad dressing for fresh soft lettuces that are coming out of farmers’ fields right now.

Eat your fresh, local raspberries while ye may! They are only around for a few short months of summer.

Check out my latest post Fruit arcana: raspberries are “caneberries” from AndrewCoppolino.com.

Wang, C., Ning, Z., Luo, N., Zhao, Z., Berg, S. J., Hwang, H., & Illman, W. A. (2026). Three‐Dimensional Analysis of Heat Tracer Transport With High‐Resolution Subsurface Heterogeneity Characterization in a Complex Aquifer System. Water Resources Research, 62(6). doi.org/10.1029/2025wr042412

CLICK HERE TO READ THE ARTICLE.

“The groundwater flow and heat transport simulations were conducted using HydroGeoSphere (Aquanty Inc, 2025). To minimize the impacts of boundary conditions, the simulation domain was assigned dimensions of 70 × 70 × 17 m with PW1 located in the center (refer to Figure 1a).”

Fig 1. Locations of monitoring wells and testing boreholes. (a) Plan view of the locations of the monitoring wells, hydraulic profiling tool logging, and nuclear magnetic resonance logging. The dashed-line square (A-B’–A’-B) delineates the area of the data domain (20 m × 20 m) for subsequent visualization of K and porosity distributions, which encompasses the wells (within a 15 m × 15 m extent). The coordinates are consistent with the simulation domain of the numerical model of heat transport. (b) Perspective view of the well screens, in which the screens for heat tracer injection, pumping, observation, and sealed intervals are highlighted in different colors. Screens numbered in black were used for observation of temperature changes during the tracer test. Tracer injection well (PW1-5) and pumping well (PW4-3) are highlighted with red and blue squares, respectively.

We're pleased to highlight this publication by Chenxi Wang and colleagues, co-authored by Aquanty's Steven Berg and Hyoun-Tae Hwang, which investigates how high-resolution characterization of subsurface heterogeneity can improve predictions of heat tracer transport in complex aquifer systems. The study leverages HydroGeoSphere (HGS) to simulate three-dimensional groundwater flow and heat transport, evaluating how different methods of representing hydraulic conductivity influence the ability to reproduce observed tracer behaviour in highly heterogeneous glaciofluvial deposits.

Accurately predicting groundwater flow and tracer transport in heterogeneous aquifers remains one of the greatest challenges in hydrogeology. Traditional approaches often rely on interpolated borehole measurements or simplified zonal representations of hydraulic conductivity, which can reproduce general hydraulic behaviour but frequently fail to capture the preferential flow paths that control tracer migration. This research addresses these limitations by comparing several characterization techniques—including permeameter testing, hydraulic profiling tool (HPT) logging, and hydraulic tomography (HT)—to determine which best represents the complex subsurface conditions governing heat transport.

The study applied HydroGeoSphere to simulate a forced-gradient heat tracer experiment conducted at the University of Waterloo's North Campus Research Site. Chilled groundwater was injected into a highly heterogeneous glaciofluvial aquifer while temperatures were monitored at multiple depths and locations throughout the subsurface. Seven different hydraulic conductivity models were then used within HGS to simulate the three-dimensional evolution of the heat plume. Results showed that models based on hydraulic tomography reproduced the observed temperature breakthrough curves and plume migration far more accurately than kriged or zonal conductivity representations, despite requiring no calibration to the transport data.

Fig 8. The simulated spatiotemporal evolution of heat tracer plumes in the plan view crossing PW1-5 and PW4-3, and three cross-sectional views of B-B’, C-C’, and D-D’. The temporal evolution of the heat tracer plume at four time points is simulated, including 3 and 13 days after chilled water injection, and 3 and 35 days after heat tracer dissipation. This heat transport simulation used the K field of model HT_8.

Key findings demonstrated that hydraulic conductivity heterogeneity is the dominant factor controlling heat tracer transport in complex aquifer systems. While variations in porosity, thermal conductivity, and mechanical dispersion influenced simulation results, accurately resolving the spatial distribution of hydraulic conductivity proved far more important for predicting preferential flow pathways and the timing of heat transport. The study also showed that hydraulic tomography can reliably characterize these heterogeneities, providing a strong foundation for predicting three-dimensional tracer movement in the subsurface.

HydroGeoSphere proved essential in enabling this work due to its ability to simulate fully coupled groundwater flow and heat transport while accounting for temperature-dependent changes in water density and viscosity. By integrating detailed hydraulic conductivity fields derived from multiple characterization methods, HGS allowed the researchers to directly evaluate how different representations of subsurface heterogeneity affect heat tracer transport without relying on site-specific calibration to tracer observations.

This research provides critical insights for groundwater characterization, contaminant transport, and shallow geothermal energy applications, demonstrating that advanced modelling approaches like HydroGeoSphere can significantly improve predictions of tracer behaviour in heterogeneous aquifer systems. By combining high-resolution field characterization with fully integrated numerical modelling, the study highlights the importance of accurately representing subsurface heterogeneity to support more reliable groundwater management and geothermal system design.

Abstract:

Accurate predictions of tracer transport in complex aquifer systems remain a formidable challenge, primarily owing to the spatial heterogeneity of hydraulic conductivity (K). Here, we conducted a forced-gradient heat tracer test within a highly heterogeneous glaciofluvial deposit, injecting chilled water and monitoring temperature at depth-specific ports, which revealed highly non-uniform, three-dimensional plume migration. To investigate whether such complex transport behavior can be reproduced with subsurface heterogeneity characterization approaches, we compared transport simulations based on several K representations: kriged and zonal K fields derived from direct-push K logging, permeameter measurements, and pumping test data, as well as hydraulic tomography (HT) results, which utilized the geostatistical inverse modeling of head response data from multiple pumping tests to map K heterogeneity. Furthermore, we employed borehole nuclear magnetic resonance logging to estimate porosity distributions. We examined the impacts of porosity, mechanical heat dispersivity, and thermal conductivity on heat tracer transport. Results showed that K heterogeneity is the key factor governing the highly variable temperature breakthrough curves observed across the monitoring network. Simulations relying on spatial correlation of borehole data were insufficient to capture the three-dimensional thermal patterns, whereas the HT-based simulations reasonably reproduced the spatiotemporal evolution of the tracer plume and delineated the advection-dominant regions, without site-specific calibration to transport data. Our findings demonstrate that HT analysis provides a reliable basis for predicting heat tracer transport behavior in complex aquifer systems.

CLICK HERE TO READ THE ARTICLE.

 The article in last Saturday's Record is titled "Long journey to transform former Kitchener industrial site almost complete". My first concern is the inaccurate or at least deceptive claim that the building was "abandoned and derelict for years," Nice try as it sat there rotting above ground and leaking trichloroethylene (TCE) below ground for many decades. The words "contaminated" and remediation" are used twice and once respectively.

What it doesn't say are the negative health effects that TCE has had on the neighbourhood, the residents and local wildlife likely since early in its life more than 120 years ago. The article also doesn't give us any idea as to the extent of remediation. Did mayor Vrbanovic  and local illuminaries ask for and receive the Cadillac cleanup as promised here in Elmira or instead did they receive the Volkswagon Beetle cleanup as we have here? TCE is a DNAPL chemical. Did they find remaining pools of TCE and if so what did they do with them? How deep did the soil and groundwater contamination go? What other chemicals were released along with the TCE? One component spills, releases and dumpings are mostly a fiction perpetrated by those looking for cleanup shortcuts. 

Where are the Phase 1 and 2 Environmental Assessments? Who did those assessments? Was a Risk Assessment completed allegedly to determine exactly how much cleanup was required? Were monitoring wells ever installed in both shallow and deeper aquifers to determine how far from the source the TCE (and other)  contamination has spread? Was any testing of nearby homes ever undertaken to determine if TCE had penetrated into them via vapour intrusion? How many cancers, lung and heart diseases may have been caused or exacerbated by TCE and other contaminants?

Sorry K-W Record but this article is simply a puff piece to help re-elect Berry Vrbanovic in October. Yes "The Shanley" probably makes the neighbourhood look better now but where was the cleanup 25 to 50 years ago when it was most needed?  As a society are we going to continue letting toxic contamination sit in residential areas for decades and pretend that no harm has been done?

Hello, friends!

I cannot complete my 10-part internship series if I do not include the “networking” aspect of it.

The internship period is assumed to be a period where you go as a baby to be spoon-fed and caressed, while in today’s competitive corporate world, it’s becoming a practice ground for the best corporate gameplay.

Today, I would discuss 4 ways how an internship could set you up to be influential beyond your work, which, in other words, we call “impactful networking”.

Imagine you’re a manager with one headcount open in six months. You’ve got a stack of resumes from strangers, and you’ve got Alex, the intern who sat next to you all summer, asked good questions, and helped Priya from the design team debug her formula at 6pm on a Thursday. You’re not going to make that decision based on a resume. You’re going to hire the person you already trust.

So the real internship project is this: become the person people already trust. Here’s how.

Most interns treat their internships like a checklist: do the assigned tasks, hit the deadlines, go home. That’s the bare minimum. The interns who get remembered are the ones who notice when someone else is drowning and quietly help out, even when it’s not their job.

Picture this:

It’s the last week of the quarter, and the marketing team is scrambling to get a report formatted before a client call in an hour. You’re a finance intern. Technically, this isn’t your problem. But you know Excel, and you see someone stressed out three desks away. You walk over and say, “Hey, want a hand with that formatting? I’m free for 20 minutes.” That’s it. That’s the whole move.

It doesn’t have to be dramatic!!
It can be as small as grabbing an extra coffee for someone who’s clearly been in back-to-back meetings, or offering to proofread a teammate’s email before they send it to a VP. None of this is in your job description. All of it is remembered.

Why it works:

People don’t build long memories around “did the job correctly". They build long memories around “went out of their way for me when they didn’t have to.” That’s the moment that sticks.

The Slack message goes out: “Team happy hour Thursday, 5pm, optional.” A lot of interns read “optional” and stay home to finish a task or just recharge. Totally understandable….

But also a missed opportunity, because “optional” work events are where the actual relationship-building happens.

Here’s why:

In a formal meeting, you’re “the intern". At a happy hour, or a team lunch, or the Friday office trivia game, you’re just a person. That’s when your manager finds out you’re both obsessed with the same TV show, or that you used to play competitive volleyball, or that you make surprisingly good small talk about airport delays. Those tiny human connections are what turn “the intern” into “our intern”, someone the team feels like they know.

You don’t need to go to everything, and you definitely don’t need to stay out past your comfort zone. But saying yes to the low-stakes stuff, the team lunch, the volunteer event, and the office softball game is one of the highest-leverage things you can do with your time. It’s networking that doesn’t feel like networking.

This is the one most interns skip, and it’s probably the most powerful.

Every person at your company has a story:

How they got there, what they wish they’d known earlier, and what a normal Tuesday actually looks like for them. Most interns never ask. They’re too focused on looking competent to realize that people love talking about themselves and that asking good questions is one of the fastest ways to build a real relationship.

So, in the next casual meeting, keep a note and ask them

• “How did you achieve this role — was this the plan, or did it happen sideways?”
• “What does a normal week actually look like for you?”
• “What do you know now that you wish someone had told you when you were starting out?”

You’ll be shocked how often people say yes to a coffee chat like this and how much they open up. A VP who seems intimidating in a big meeting might turn out to be someone who started in the mailroom and has a genuinely great story to tell — if anyone bothers to ask.

Why it works:

Curiosity is flattering. When you ask someone about their path, you’re implicitly saying, "Your experience matters to me.” That’s rare, and people remember who made them feel that way.

This is the step almost everyone forgets, and it’s the one that actually pays off months later.

Say your internship wraps up in August. In October, you see an article about a project your old team was working on. Send it to your manager with a one-line note: “Saw this and thought of the project we were on this summer; hope it’s going well!” That’s a 30-second email. It costs you nothing. And it keeps you on their radar for exactly the moment when a full-time role opens up.

Connect with people on LinkedIn before your last day, not with a generic request but with a short note referencing something specific you worked on together. Send a thank-you note to your manager. If someone gave you real career advice during your internship, tell them a few months later how it played out. People remember who stayed in touch and who disappeared the second the badge stopped working.

Why it works:

Hiring decisions are about recency as much as merit. If you vanish after your last day, you’re relying entirely on someone remembering you months later, unprompted. If you check in occasionally, you’re doing the remembering for them.

Competence gets you through the door. Relationships get you the offer. Doing good work is the baseline, not the differentiator.

Small, unglamorous acts of helpfulness compound. Helping with something outside your role costs you little and is remembered far longer than you’d expect.

“Optional” social events are actually high-value work. They’re where you stop being “the intern” and start being a known, trusted person on the team.

Curiosity is an underrated networking tool. Asking people about their career path is easy, low-pressure, and genuinely builds connection.

Networking doesn’t end on your last day. A few well-timed check-ins after your internship can be the difference between being forgotten and being the first call when a role opens up.

At the end of the day, networking is about being a decent, curious, helpful person for a few months and letting that speak for itself.

How to Network at Your Internship (Without Feeling Fake About It) was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Making bread was my first foray into a long-time love of not only food history but some of the science behind it and why things cook well – or don’t. Unlike putting together a dish with a protein, starch and some veg, baking and pastry demands attention to science. Or else it fails.

Let me give you one example of such a failure that resulted from a baking ratio being wonky and off-kilter: my attempt years ago at a special dessert for a fall dinner service, clafoutis.

As Michael Ruhlman’s excellent book has it, cooking is about basic (and accurate) ratios rather than recipes, per se, and the fundamental techniques, properly executed, that determine the success of a dish — even if it’s merely a simple sheet pan of scrumptious brown-butter chocolate chip cookies that you’re baking off.

I learned this the hard way in a restaurant kitchen — before Ruhlman’s book existed — by way of a rustic dish from Limousin.

A region of southwest-central France (where Limousin beef cattle are from), clafoutis is a tart-like dessert that I had made at home successfully a number of times; it can either be slightly cake-like in texture, or it can take on a thicker pudding-like consistency; the latter of which was my goal at the restaurant.

First some background: in the Limousin countryside, clafoutis is traditionally a cherry dessert, but it can be made with just about any fruit. The technique is simple: you basically pour the batter over the fruit and bake it, serving it slightly warm with a dollop of whipped cream – and if you’re into gilding the lily using a fine-meshed sieve to give it a liberal showering of confectioner’s sugar as further garnish.

In this dessert, though, I need to provide an important safety note: in the traditional Limousin cherry clafoutis, the cherries are cooked with their pits. There is a good reason for this from a culinary technique point of view: whenever you cook with fruit that has a pit, the combination of the two creates a more robust flavour. In cherries, that’s a slight tinge of clove and almond that is created by a variety of chemicals, the names of which I don’t know, in the pits (a cherry is known as a drupe) which are activated when they are being baked at 350F.

All of that makes the cherry clafoutis à la Limousin extremely delicious – but from a dental point of view, it’s not really a good way to serve customers for fear of their cracking a tooth — something that doesn’t look good on a Google review.

Of course, I didn’t want to risk that and defaulted to the very tasty and less tooth enamel-threatening blueberry (although those do stain teeth quite well).

My dessert, because I botched the calculation of reducing the recipe for a single large clafoutis tart into multiple individual servings, baked into something quite solid – even the blueberries.

The Chef came over to inspect my clafoutis work, poked at the ramekins a bit and then (in a moment that I will grant a wonderfully understated and gentle sarcasm) delivered with an arched eyebrow a brilliant piece of wise-acre marketing: “Call them Blueberries Coppolino.”

But I got it: it was clearly a sign that these calamitous clafoutis could not be sent out for dessert.

Damn ratios.

[Image/David Loong]

Check out my latest post Blueberry clafoutis and ratios from AndrewCoppolino.com.

Today's K-W Record has a large Opinion article by Luisa D'Amato on page A3 titled " Something big is happening at Wilmot's industrial megasite. Why are we in the dark?" Personally I find the timing very telling. Remember the haste to prematurely cut the corn crop in one of the fields a year or two ago? That seemed to be sending a message to critics which was we the Region bought the field and we'll do with it as we please. Now just two months before municipal elections I have to wonder if the increase in activity including removing buildings, hiring security guards to patrol access roads and archeologists on site doing research is to defeat any negative response by citizens at the upcoming polls. Are regional councillors afraid that the election might actually reverse the process if citizens kick all the bums out of office?

As Luisa D'Amato indicates, a non-disclosure agreement prior to the bulk of the land being assembled might be justified on the basis of land costs being affected, but after the fact seems unreasonable. It is unreasonable because the public who are actually footing the bills have a right to know how this project "...will affect our environment, our food security, our water supply and our road and sewer infrastructure."  To date all requests for studies such as traffic, wildlife,  declining farmland capacity, electrical usage and water supply needs and capabilities have all been ignored. That is grossly unacceptable and exactly why those buggars need to be fired by their employers (i.e. us). 

Add to all that is the recent recognition of the frailty of our water system in Waterloo Region. This proposed megasite is close to the Wilmot Centre Wellfield which is already under enormous pumping pressure plus hampered by high Nitrates contamination. Ms. D'Amato mentions the concerns around a chemical spill. This is why subsurface stratigraphic conditions directly beneath the megasite need to be publicly published as well as the overlying soil/clay/sand/gravel above the wellscreens for the Wilmot Centre Wellfield. My recollection is that there are parts of the Waterloo Moraine in Wilmot Township with minimal to no clay aquitards between the ground surface and the predominate two aquifers beneath. Those areas are extremely vulnerable to chemical spills and could quickly finish off any hope of continued groundwater usage in large parts of Waterloo Region.

What if we viewed workplace culture as a garden?

That’s the metaphor Abi Adamson used in her closing keynote at the International Allyship Day conference hosted by Next Pivot Point earlier this week.

Adamson gave us a peek at her upcoming book Culture Blooming: Nurturing Workplaces Where People Grow. In her garden metaphor, each person needs the right conditions to thrive.

And while we may not be able to control the “soil” of our organization (the policies, practices, and cultural toxins), we can control the “light.”

We can pay attention to who gets seen, heard, credited, and given career-making opportunities. And make sure people aren’t left to wither in the shadows.

Here are a few ways to put that into practice:

• Speak their name when they aren’t in the room. Advocate for coworkers in the decision-making rooms where they aren’t present.
• Give them credit. Publicly acknowledge their ideas, contributions, and expertise.
• Bring them along. Invite a colleague to join a high-profile meeting to help them gain visibility and exposure to senior leaders.
• Distribute stretch assignments fairly. Make sure access to high-profile projects and task forces isn’t limited to the same “go-to” people.

Who on your team could use a little more light? And what can you do to shine it their way?

Share this action on Instagram, LinkedIn, or YouTube.

Sponsor 5 Ally Actions and put your brand or business in front of 40,000 caring individuals in business, healthcare, education, and non-profits.

Or, say thanks to Karen and buy her a coffee ☕.

Jeepers. New research suggests that AI can develop its own biases from experience and stereotype job applicants even more readily than humans do.

Researchers at Princeton University and the University of Chicago put large language models (LLMs), including ChatGPT, Claude, and Gemini, through a simulated hiring game with four fictional ethnic groups. The LLMs quickly began sorting candidates from different groups into different jobs based on early observations.

For example, when a candidate from one ethnic group failed as a doctor, the models began avoiding other candidates from that group for doctor roles. Instead, they started hiring them to lower-status jobs, such as janitorial work.

The models learned a stereotype from limited evidence and then generalized it to an entire group.

AI can be a powerful tool, but we can’t let it introduce more bias into our hiring decisions than we already have (which is too much).

If your organization is using AI to evaluate candidates, share this research. Ask whether AI is actually helping with the task. And start a conversation about what checks and balances are needed to help prevent further bias in the hiring process.

During the 25 years I worked in the tech industry, my managers always held one-on-one meetings with me. Sometimes they were weekly, sometimes less frequent. Regardless, I relied on them to keep my manager informed, ask for advice, and get help removing roadblocks.

I also got plenty of positive reinforcement about the things I was doing well, along with constructive suggestions for how to get better. I’m not sure how I could have effectively done my job or grown in my career without the feedback I received in these meetings.

You know what else? I would have been angry if my manager had scheduled one-on-one meetings with others on my team, but not with me.

While that’s not something I have experienced, many have. In Being Black In Corporate America, Coqual uncovered 14 specific microaggressions that Black employees experience at significantly higher rates than all other racial groups surveyed. One is, “My manager has met one-on-one with others on my team, but not with me.”

Don’t be that manager.

What story are your images telling?

We send subtle messages whenever and wherever we use images. In presentations and pitch decks. In marketing collateral. In blog posts, websites, and recruiting material. If we consistently show one type of person as the leader, expert, or successful employee, we may inadvertently reinforce stereotypes about who belongs in those roles.

So, the next time you choose a stock photo or use AI to generate an image, take a closer look. Ask yourself, who is represented and who is missing?

And, are you portraying people authentically and respectfully?

I recently updated my list of favorite stock photography resources to include All In Frame, a free stock photography collection led by disabled creatives to help marketers, advertisers, and creative teams tell more authentic stories about disability.

I especially appreciate this guideline from their Terms of Use:

“You may not use the image in any context that demeans, stereotypes, exploits, misrepresents, or otherwise harms the dignity, rights, or lived experience of disabled people or any person depicted in the image.”

While I wish the guideline wasn’t needed, I appreciate the reminder that representation matters and it should be done with respect.

I heard from a subscriber whose coworker announced a new productivity tool called “Master Aggregate.”

She reached out to him and asked, “Could we call it something other than ‘master’?”

Then she used one of my favorite techniques for better allies: give feedback by sharing what you’ve learned.

She explained that she’d learned the term “master” isn’t the most inclusive choice from a historical perspective, and often isn’t the clearest way to describe what we’re trying to say.

As an alternative, she suggested the phrase “Synced Aggregate.”

Her coworker thanked her and immediately changed the tool’s name.

Made. My. Day. 🙏

If you’ve taken a step towards being a better ally, please reply to this email and tell me about it. And mention if I can quote you by name or credit you anonymously in an upcoming newsletter.

That’s all for this week. I’m glad you’re on this journey with me,

Karen Catlin (she/her), Author of the Better Allies® book series

100% written by me. I use AI for researching a personal archive of my books and past newsletters, and for light editing.

Copyright © 2026 Karen Catlin. All rights reserved.

Together, we can make a difference with the Better Allies® approach.

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Control the Light, and Other Actions for Allies was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

You know I'd like to fill out a survey that I had some confidence was actually honest and above board. One that for example I could see my survey responses at some later date had not only been received but kept as part of the documentation on file. Do I really believe that my or anybody else's comments have actually been taken to heart by regional staff or politicians? Not a hope. 

The survey I filled out today was advertised in the K-W Record and is the second that I have completed. It makes me wonder what the results of the first survey were. Is the Region hoping to come off looking better simply by their proposed new procedure that was in yesterday's newspaper and probably introduced at regional council the day before? If their ratings have already risen does that mean that they can then backtrack by the five councillors of the appeal group deciding to automatically torpedo 95% of all appeals coming their way?

Surveys and dog and pony shows such as past regional games playing and likely the latest "public information and consultation session"  scheduled for August 20/26 are not true public consultation. Public consultation is less scripted and more public. Citizens ask questions from a microphone so that all present can hear their questions and then also hear the responses back from whomever is representing the government or industry behind the public meeting. Something like that would be worth attending. Private one on one discussions with staff are a waste of time and do nothing.

Imagine you read the following sentence:

The trophy didn’t fit in the suitcase because it was too big.

What does “it” refer to?

The trophy?

Or the suitcase?

Most of us answer that question almost instantly without consciously thinking about it. Somehow, our brain knows which earlier words are important.

Large Language Models face exactly the same challenge.

Before predicting the next token, the model first needs to figure out which earlier tokens matter the most. Not every word contributes equally to the meaning of a sentence. Some words carry the core meaning, while others provide little useful information.

This ability to identify the most relevant parts of a sentence is called self-attention, and it’s one of the key innovations that made modern language models so successful.

Instead of treating every earlier word equally, the model learns to focus on the ones that provide the most useful information.

In this article, we’ll build an intuitive understanding of self-attention without diving into heavy mathematics. By the end, you’ll understand why the Transformer architecture changed natural language processing forever.

Before Transformers, many language models processed text one word after another.

Imagine someone reading a book while trying to remember every previous sentence. As the story becomes longer, remembering details from earlier chapters becomes increasingly difficult.

Earlier neural network architectures faced a similar challenge. Although techniques like LSTMs and GRUs improved long-term memory, they still struggled with capturing relationships between words that were far apart in a sentence.

Consider this sentence:

The animal didn’t cross the road because it was tired.

When we read the word it we immediately understand that it refers to the animal.

For a machine, making that connection isn’t obvious.

The model needs a way to look back at the sentence and decide which earlier words matter most.

That is precisely what self-attention was designed to do.

Imagine you’re attending a meeting with ten people.

At the end of the discussion, someone asks:

Who approved the budget?

You don’t replay every sentence spoken during the meeting.

Instead, your brain immediately focuses on the finance manager because that’s the person most likely to have the answer.

Your attention naturally filters out information that isn’t relevant.

Self-attention works in a similar way.

Instead of treating every token equally, the model asks:

Which previous tokens should I pay attention to before making my next prediction?

Every token examines the other tokens in the sentence and decides how much importance each one deserves.

Some receive a great deal of attention.

Others receive very little.

At first, this raises an interesting question.

If every token can look at every other token, how does the model know which word came first?

Self-attention alone doesn’t understand word order.

That’s why Transformers add positional encoding, which gives every token information about its position in the sentence before attention is calculated. Positional encoding and self-attention work together — one tells the model where a token appears, while the other helps decide which tokens matter most.

Without positional encoding, the sentence:

Dog bites man

would look almost identical to

Man bites dog.

Let’s look at a simple sentence.

The cat sat on the mat.

When processing the token sat, the model doesn’t only look at the previous word.

Instead, it considers every token in the sentence.

An example attention distribution might look like this:

| Token | Attention |
|-------|----------:|
| The   | 5%        |
| cat   | 60%       |
| sat   | 20%       |
| on    | 10%       |
| mat   | 5%        |

The model isn’t reading the sentence strictly from left to right.

Instead, it builds relationships between all tokens simultaneously.

This ability to connect distant words is one of the biggest reasons Transformers outperformed earlier language models.

How does the model decide which words deserve more attention?

It calculates an attention score between every pair of tokens.

A higher score means one token is more relevant to another.

Imagine the scores looked like this:

cat -> sat = 0.82

cat -> mat = 0.11

cat -> the = 0.07

These numbers aren’t manually programmed.

During training, the model gradually learns which relationships are useful for making accurate predictions.

After seeing billions of examples, it becomes remarkably good at identifying important connections.

Most explanations of self-attention immediately introduce three unfamiliar terms:

• Query
• Key
• Value

That can make the idea seem much more complicated than it really is.

Instead, let’s first understand why these concepts exist.

A useful analogy is searching for a book in a library.

Imagine you’re looking for a book about machine learning.

• Your search request is the Query.
• Every book has a label describing its topic. That’s the Key.
• The contents inside the matching book are the Value.

You compare your search request with every book label.

The closer the match, the more likely you are to open that book.

Self-attention works almost the same way.

Each token creates:

• a Query describing what information it’s looking for
• a Key describing what information it offers
• a Value containing the information that will actually be shared

The model compares every Query with every Key.

The better the match, the more influence that token’s Value has on the final representation.

You can think of Query, Key, and Value as a search engine.

The Query represents what the token is looking for.

The Key describes what information another token offers.

The Value contains the information that can be shared.

Although the underlying mathematics involves matrix multiplication and dot products, the core idea is surprisingly intuitive:

Tokens that are more relevant to each other receive more attention.

Looking at language from a single perspective isn’t always enough. Language contains many different types of relationships.

Imagine asking a group of experts to analyze the same sentence.

One focuses on grammar.

Another looks for relationships between subjects and verbs.

Another tracks pronouns.

Another searches for long-distance connections.

Multi-head attention works in a surprisingly similar way.

The outputs from all attention heads are then combined before passing to the next Transformer layer.

Self-attention solved several problems that earlier language models struggled with.

It allows every token to interact directly with every other token in the sequence, making it much easier to capture long-range relationships.

Unlike recurrent models, Transformers can process all tokens in parallel during training, significantly improving training efficiency on modern hardware.

Because of these advantages, self-attention became the foundation of today’s Large Language Models.

Self-attention does have one important limitation.

Every token compares itself with every other token.

As the input becomes longer, every token has to compare itself with more tokens, causing the amount of computation to grow rapidly.

That’s one reason researchers continue developing more efficient attention mechanisms for long-context models.

Whether you’re using GPT, Claude, Gemini, Llama or DeepSeek, they all rely on this same fundamental idea.

Not exactly.

Self-attention helps the model decide which parts of the context deserve the most focus.

It does not mean the model understands language the way humans do.

The model still learns statistical patterns from enormous amounts of text.

Self-attention is simply one mechanism that makes those learned patterns far more useful.

Self-attention is memory.

Not quite. Attention determines which tokens are most relevant at the current moment.

Memory is a broader concept involving the model’s parameters and its context window.

Every token receives equal attention.

No. Different tokens receive different attention scores depending on the context.

Self-attention alone makes Large Language Models intelligent.

Self-attention is one important component. Embeddings, positional encoding, feed-forward networks, training data, optimization algorithms, and massive computational resources all contribute to the model’s capabilities.

• Every token can attend to every other token.
• Attention scores are learned during training.
• Queries, Keys, and Values determine how attention works.
• Multi-head attention captures different types of relationships.
• Self-attention is one of the core ideas behind every Transformer model.

Self-attention solved one of the biggest challenges in language modeling:

How can a model decide which earlier words matter most?

Instead of reading text one token at a time and hoping important information isn’t forgotten, Transformers allow every token to examine the entire context before making a prediction.

That simple shift completely changed modern AI.

Today, every time ChatGPT generates a response, millions of attention calculations happen behind the scenes.

Before making a prediction, every token effectively asks:

Out of everything I’ve seen so far, what deserves my attention right now?

The answer to that question guides the model toward its next prediction.

Once you understand self-attention, ideas like Transformers, inference, context windows, and even AI agents become much easier to understand because they all build on this same foundation.

How Self-Attention Works in Large Language Models: Explained with Simple Examples was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

Think about a classroom during attendance.

Each student is assigned a roll number:

• Roll No 1 → Rahul
• Roll No 2 → Priya
• Roll No 3 → Arjun
• Roll No 4 → Sneha

Now suppose the teacher wants to know:

“Who is Roll No 25?”

The teacher doesn’t need to read every student’s name before that. Since each student already has a position, they can directly look up Roll №25.

Arrays work similarly. Every element has a position (index), allowing quick access. That ability to access information by its position is one of the reasons arrays are so useful.

What’s interesting is that most developers start using arrays long before they formally learn Data Structures and Algorithms. Whenever you’ve worked with a list of users, products, notifications, messages, comments, or transactions, you’ve likely been using arrays without giving them much thought.

Arrays are everywhere because a large number of real-world applications deal with collections of similar pieces of data. Whether you’re displaying products on an e-commerce website, showing notifications in a mobile app, or rendering search results on Google, chances are an array is involved somewhere behind the scenes.

Understanding arrays is important because they are not just another data structure. They are the foundation on which many other DSA concepts and problem-solving patterns are built.

An array is a data structure that stores multiple values under a single variable name.

Imagine having to store the names of students in a classroom without arrays:

const roll_No1 = "John";
const roll_No2 = "Sarah";
const roll_No3 = "Mike";
const roll_No4 = "Emma";

This works when there are only a few users, but it quickly becomes difficult to manage as the list grows.

Arrays solve this problem by allowing us to group related values together:

const students = ["John", "Sarah", "Mike", "Emma"];

Instead of managing four separate variables, we now have a single array that contains all the users.

Each value inside the array is assigned a position known as an index. One thing that need to remember is that array indexing starts from 0, not 1.

const students = ["John", "Sarah", "Mike", "Emma"];

console.log(students[0]); // John
console.log(students[1]); // Sarah
console.log(students[2]); // Mike

Here, "John" is stored at index 0, "Sarah" at index 1, and "Mike" at index 2.

This idea of assigning a position to every element is what makes arrays so powerful.

Let’s go back to our classroom example.

Suppose a teacher wants to know who has Roll No 50. The teacher doesn’t need to start from Roll No 1 and count all the way to 50. Since every student already has an assigned position, they can directly look up Roll No 50.

Arrays work in much the same way.

Because every element has an index, the computer can directly access the required position instead of searching through the entire collection.

const numbers = [10, 20, 30, 40, 50];

console.log(numbers[3]);

When we ask for numbers[3], the computer doesn't start from the beginning and count its way to the fourth element. It already knows exactly where that position is located and can retrieve it immediately.

Whether the array contains 5 elements or 5 million elements, accessing an element by its index requires essentially the same amount of work.

That’s why array access is considered O(1), also known as constant time complexity. The size of the array doesn’t affect how quickly the element can be retrieved.

Now that we understand how arrays are organized, let’s connect them to the complexity concepts we discussed in Episode 1.

Some array operations are extremely fast, while others become more expensive as the array grows.

Understanding why these complexities differ is much more valuable than simply memorizing them.

Suppose we want to access the element at index 5:

arr[5]

Since every element in an array has a fixed position, the computer can directly jump to that location and retrieve the value.

There is no need to check the elements before it or search through the array.

That’s why accessing an element by index takes O(1) time.

Now consider a different problem. Instead of asking for a specific position, we’re looking for a specific value.

const arr = [10, 20, 30, 40, 50];

Suppose we want to find the value 50.

The computer has no way of knowing where that value is located, so it starts checking the elements one by one.

Is it 10?
Is it 20?
Is it 30?
Is it 40?
Is it 50?

In the worst case, the value might be at the very end of the array, or it might not exist at all. That means every element may need to be inspected.

As the array grows, the amount of work grows as well, which gives us a time complexity of O(n).

Adding a new element to the end of an array is usually straightforward.

[10, 20, 30, 40]

Insert 50:

[10, 20, 30, 40, 50]

Nothing else needs to move, so this operation typically takes O(1) time.

Now let’s insert a value at the start of the array.

[10, 20, 30, 40]

Insert 5:

[5, 10, 20, 30, 40]

From our perspective, this looks like a simple operation. Internally, however, every existing element must shift one position to the right to make space for the new value.

10 → moves to index 1
20 → moves to index 2
30 → moves to index 3
40 → moves to index 4

The larger the array becomes, the more elements need to be moved.

That’s why inserting at the beginning has a time complexity of O(n).

A similar situation occurs when we remove the first element.

[10, 20, 30, 40]

Remove 10:

[20, 30, 40]

After the deletion, every remaining element must shift one position to the left to fill the gap.

Because the amount of work grows with the size of the array, deleting from the beginning also takes O(n) time.

The key takeaway is that arrays are incredibly efficient when you know exactly where the data is located, but operations that require shifting many elements can become expensive as the array grows.

Let’s start with one of the most common array problems.

Given an array of numbers, find the largest value present in it.

Input:

[5, 9, 2, 15, 7]

Output:

15

Imagine all the numbers are placed on a table.

Instead of comparing every number with other numbers, we can keep track of the largest number we’ve seen so far.

We start by assuming the first number is the largest. Then, as we move through the array, we compare each number against our current largest value. Whenever we find a bigger number, we update it.

By the time we reach the end of the array, the value we’re holding will be the largest number in the entire array.

function findLargest(arr) {
  let largest = arr[0];
    for (let num of arr) {
      if (num > largest) {
        largest = num;
      }
    }

  return largest;
  }

Array = [5, 9, 2, 15, 7]

Start:
largest = 5

5 > 5 ? No
largest = 5

9 > 5 ? Yes
largest = 9

2 > 9 ? No
largest = 9

15 > 9 ? Yes
largest = 15

7 > 15 ? No
largest = 15

Answer = 15

We traverse the array exactly once, checking each element against the current largest value.

• Time Complexity: O(n)
• Space Complexity: O(1)

The time complexity is O(n) because every element is visited once. The space complexity is O(1) because we only use a single variable, largest, regardless of how large the array becomes.Pattern Behind This Problem

This problem introduces one of the most fundamental patterns in Data Structures and Algorithms: Linear Traversal.

In this problem, we start at the beginning of the array and examine every number exactly once while keeping track of the largest value we’ve seen so far. While traversing, we can perform whatever operation the problem requires, such as finding a maximum value, counting elements, calculating a sum, or checking a condition. Although the pattern seems simple, it appears surprisingly often. You’ll encounter it while working with arrays, strings, linked lists, trees, and many other data structures.

As we move through this series, we’ll build on this foundation and explore more advanced patterns that evolve from the same basic idea.

Consider the following array:

[2, 5, 8, 11, 14, 19]

We need to count how many even numbers are present in the array.

The answer is:

3

because 2, 8, and 14 are even.

Before writing any code, think about what information we actually need. The problem is asking for the count of even numbers, not the numbers themselves. That means there is no need to store even numbers we find.

Instead, we can start with a counter set to 0 and traverse the array one element at a time. Whenever we encounter an even number, we increment the counter by one. By the time we reach the end of the array, the counter will tell us exactly how many even numbers are present.

Instead of storing every even number, we only need a count.

Start with zero.

Whenever you encounter an even number, increase the count.

Continue until the array ends.

function countEvenNumbers(arr) {
  let count = 0;
  for (let num of arr) {
      if (num % 2 === 0) {
        count++;
      }
    }
    return count;
  }

Again, every element is visited once.

Time Complexity: O(n)

Space Complexity: O(1)

Behind this solution is the same Linear Traversal pattern that we saw in the previous problem. We move through the array one element at a time and perform a small piece of work for each element.

However, this problem introduces another important concept: maintaining a running value.

Instead of storing every even number we encounter, we keep track of only the information we actually need. In this case, that information is the count of even numbers, so we continuously update a single variable as we traverse the array.

This idea shows up frequently in DSA. Whether you’re calculating a running sum, tracking a maximum value, counting occurrences, or maintaining a window of information, the underlying approach is process each element and keep updating a variable that represents the current state of the solution.

At first glance, arrays might look simple.

In fact, many developers underestimate them because they are usually the first data structure we learn.

But arrays are the foundation for a huge portion of Data Structures and Algorithms.

Many popular patterns begin with arrays:

• Linear Traversal
• Two Pointers
• Sliding Window
• Prefix Sum
• Binary Search
• Hashing
• Kadane’s Algorithm

The important thing is to recognize that arrays are where these patterns start.

Once you’re comfortable traversing arrays and understanding their complexity, learning those patterns becomes much easier.

For anyone interested in practicing further, here are a few LeetCode problems that align well with the concepts covered in this episode.

1480. Running Sum of 1D Array

1732. Find the Highest Altitude

2011. Final Value of Variable After Performing Operations

485. Max Consecutive Ones

414. Third Maximum Number

A Little More Challenging

724. Find Pivot Index

121. Best Time to Buy and Sell Stock

53. Maximum Subarray

697. Degree of an Array

1748. Sum of Unique Elements

In the next episode, we’ll explore the Two Pointers pattern and discover why having two positions moving through an array can often be more useful than having just one.

Arrays: From Classroom Attendance to Algorithms was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

KITCHENER - Yosvani Penalver only had one hit on the night, but it provided the momentum swing the Kitchener Panthers needed.

Down 2-0, he hit a three-run home run in the third inning and Kitchener never looked back in a 7-5 win over the Toronto Maple Leafs Thursday night at Jack Couch Park.

The Panthers scored three more in the fourth, two of which came off the bat of Malik Williams. His two-run single extended the lead, while Williams reached a milestone with his 100th career RBI.

Jorge Minyety got the win, striking out three in six innings of work. He gave up two runs on four hits, including a first inning solo homer from Yasiel Puig.

Jacob Liberta gave up three runs (two earned in the ninth), and Toronto did get the tying run to the plate, but the lefty reliever wrapped things up.

Kitchener improves to 14-26 on the season, while Toronto dropped to 12-24.

The Panthers hit the road to Welland on Saturday, before playing four of their next five at home. The next home game is Sunday at 2:05 p.m. against Barrie.

Kitchener will sport special jerseys on Sunday, commemorating Orange Shirt Day to honour the National Day for Truth and Reconciliation.

GET YOUR TICKETS NOW and #PackTheJack!