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Taking Kaepernick’s lead, Black athletes increasingly forcing change in pro sports

It was four years ago, in 2016, when Colin Kaepernick kneeled, and his NFL career came crashing down.

Kaepernick is now 32, and commissioner Roger Goodell says the QB would be welcomed back, encouraging teams to sign him. He said the NFL “was wrong” for not listening to player protests against racism earlier. Goodell didn’t give a reason for why Kaepernick hadn’t been signed in any of the previous three seasons.

On Wednesday, Los Angeles Chargers coach Anthony Lynn said Kaepernick fits his team’s system and is on their emergency workout list.

Kaepernick’s protest against racism and police brutality in the U.S. — topics that have once again risen to the forefront in the wake of George Floyd’s death on May 25 at the knee of a white Minneapolis police officer — worked in a couple of ways.

WATCH | CBC Sports’ Jamie Strashin discusses increased activism among Black athletes:

CBC Sports’ Jamie Strashin reports on Black athletes finding their voice amid the rising racial tension. 1:45

For one, it sparked conversation. It also showed the power imbalance Kaepernick was protesting against. The quarterback accounted for 85 touchdowns and just 30 interceptions in 69 games with the San Francisco 49ers. Twelve of those games came in the season he turned 29, when he began kneeling during the American anthem.

In a league featuring just two minority principal team owners (Jacksonville’s Shahid Khan and Buffalo’s Kim Pegula, who co-owns the team with husband Terry), Kaepernick has yet to play another game.

A joint lawsuit against the NFL with former 49ers teammate Eric Reid, claiming the two had been blacklisted for protesting, was settled in February 2019.

Goodell was spurred to speak about Kaepernick in recent weeks after a group of star NFL players, including quarterbacks Patrick Mahomes and Deshaun Watson, posted a video about racial inequality directed at the league.

“I think that’s very telling that the athlete propels him into speaking. But he still is kind of walking up and stopping short of the line of acknowledging Colin and his blackballing and the particular protest that he was mounting,” said Amira Rose Davis, a professor of history and African-American studies at Penn State University.

“And I think it’s a testament to how things have certainly shifted. But at the same time, it’s revealing what work is left to be done.”

Howard Bryant, an ESPN writer, said the presence of those star quarterbacks pushed the league to finally say something.

“Anyone who knows a thing about the National Football League knows that player power runs through the quarterback. And to have a quarterback [Mahomes] who not only won the Super Bowl, but a quarterback who might be the best player? Oh, that’s got us there. The absolute icon of the league,” Bryant said.

WATCH | Roger Goodell says NFL should have listened to player protests:

Consider: Super Bowl MVP Mahomes, two-time Pro Bowler Watson, reigning MVP Lamar Jackson and Dallas Cowboys starter Dak Prescott have all debuted since Kaepernick first took a knee.

Before them, white quarterbacks like Tom Brady, Peyton Manning, Aaron Rodgers and Drew Brees were typically the league’s leading voices.

Now that the NFL’s most marketable stars are speaking out on the league’s racial imbalance first addressed by Kaepernick, Goodell is forced to answer publicly.

“This is not going to go away unless they deal directly head-on with Colin Kaepernick,” Bryant said.

NFL leadership has also been questioned, with just three Black head coaches in a league where 70 per cent of the players are Black.

Canada’s Hubbard uses his platform

Bryant said the racial imbalance seeps into the U.S. college football game, too, where well-compensated white coaches make millions of dollars off the performances of their mostly Black, but all uncompensated, athletes.

“They don’t care about where they come from. They care about their mission. And they feel that they’re able to essentially enrol the players and the players are not going to push back. How far can you push?” he said.

Canadian running back Chuba Hubbard, who plays at Oklahoma State under coach Mike Gundy, threatened a boycott of the program on Monday after a picture surfaced with Gundy wearing a One America News T-shirt. OAN is a far-right U.S. news network.

Oklahoma State’s Chuba Hubbard carries the ball during a November 2019 game. Hubbard recently called out coach Mike Gundy for wearing a controversial T-shirt. (Chris Jackson/The Associated Press)

Within hours, a video from the school was released including Hubbard and Gundy, in which Hubbard apologized for going about his grievance the wrong way. Davis said the apology is proof of how power works.

“He’s standing there saying sorry — sorry for what, I wanted [to know]. For what exactly?” Davis said.

The next day, Gundy posted another video with a fuller apology for wearing the controversial T-shirt.

“I think that’s more of what you’ve been seeing this moment. And you have more people willing to uplift [Hubbard] and say, ‘Listen, you don’t have to back away from that.’ But I think that I mean that was also a very revealing moment, because it only goes so far,” Davis said.

Still, Hubbard may have felt comfortable even voicing his opinion because of the protests and mass sharing of stories in the weeks since Floyd’s death.

“There’s a convergence of interests where all of a sudden people who might have been able to look away before haven’t been able to look away. And I think what that has meant is that organizations have been compelled to say something. The needle has moved. They have to act,” Davis said.

Causing change at the top

In soccer, the English Premier League returned Wednesday with each player wearing jerseys that said, “Black Lives Matter” instead of their name on the back. Teams also kneeled when the whistle blew to start the game for several seconds in protest of racism worldwide.

Both moves were greenlit by the league at the request of players.

WATCH | EPL players kneel at kickoff:

Aston Villa and Sheffield United players took a knee at kickoff in support of the “Black Lives Matter” movement as the Premier League season restarted on Wednesday. 2:00

Back in 2016, American women’s soccer star Megan Rapinoe kneeled during the anthem in solidarity ahead of an NWSL game. The country’s sport federation condemned the move at the time but repealed its ban against kneeling last week.

Rapinoe’s teammate, Crystal Dunn, said Tuesday she didn’t kneel at the time because as a Black woman on the roster bubble, she was worried about her job. It is telling that Dunn only felt comfortable giving her reasoning now.

“I think that this moment has given cover for athletes who might not have been empowered to be vocal before to really raise their voices collectively. And when you see collective kind of labour action like that, you see response videos. You see people needing to actually engage with athletes in a different way,” Davis said.

In the NBA, notable players like Kyrie Irving and Dwight Howard have suggested that restarting the season could take away from the current Black Lives Matter movement. In response, the league called it a “central goal” to bring attention to “combating systemic racism.”

“One of the reasons why the NBA looks on its face a little different from the NFL is because the biggest stars in the NBA from five, six years ago were very vocal,” Davis said.

“The biggest stars in the NFL, particularly the white quarterbacks, were not as vocal. [They] were not vocal at all. And I think that that’s one of the things is the NBA followed its superstars and the NFL could take steps to shut things down.”

For the NFL, that may no longer be the case.

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CBC | Sports News

Pediatric allergist traces ‘mystery’ reactions to pea protein — an increasingly popular ingredient

As a pediatric allergist, Dr. Elana Lavine often advises parents to avoid peanuts, eggs and seafood. Now, she’s warning them that allergies can also be triggered by “pea protein” found in a growing number of foods.

Lavine described what happened to a two-year-old patient after eating non-dairy yogurt.

“When given the yogurt, they had a full-blown anaphylactic reaction in the aisle of the grocery store,” she said.

The girl has an allergy to peanuts and tree nuts, but her parents had no idea what caused the yogurt reaction.

Neither did Lavine. But following the yogurt mystery, she learned of other patients who’d had unexplained reactions. She gathered details of their cases and eventually identified the culprit: pea protein.

Split peas are a type of field pea grown for drying. They contain pea protein, an increasingly popular substitute for meat protein, and a potential allergen. (Craig Chivers/CBC)

The protein, which is extracted and concentrated from peas, is popping up in all sorts of products on grocery store shelves, often as a substitute for meat protein. It’s used in vegan cheeses, yogurts and milk substitutes.

Lavine estimated 95 per cent of patients with peanut allergies can tolerate peas. But for the other five per cent who can’t handle exposure to pea protein, it can be life threatening.

Lavine was so concerned about the reactions her patients described, she wrote a case study about them in the Journal of Allergy and Clinical Immunology. The yet-to-be released paper warns parents and doctors to be vigilant.

Dr. Elana Lavine wants to raise awareness of how pea protein is now found in more foods and may trigger allergic reactions. (Craig Chivers/CBC)

Producers consider pea protein to be a cheap, sustainable alternative to meat protein.

But pea protein lacks one essential amino acid needed to make it a complete protein, said Alison Duncan, a professor of human health and nutritional sciences at the University of Guelph. A complete protein contains all nine essential amino acids that humans need.

“There’s no doubt that the pea protein extracts are high in protein,” said Duncan, a registered dietitian. “It’s not a so-called complete protein like soy is.”

Pea protein is usually derived from yellow peas. To extract the protein, the pea is mixed with water. The fibre and starch are then removed, leaving only the protein. When the protein powder is added to foods, it’s in a concentrated form.

“It concentrates the protein from a large number of peas into a small amount,” Lavine said, and that concentration can cause a much more severe reaction than eating plain peas.  

Pea protein is listed in the ingredients but it does not have to be flagged as an allergen in Canada. (CBC)

The protein is also being added to some meat and dairy products to boost the protein level, said Rotimi Aluko, a food chemist and professor at the University of Manitoba.

The use of pea protein allows these companies to increase the protein levels in their products while keeping their costs down, Aluko said.

“Pea protein has very superb function that allows the manufacturer to formulate delicious foods, and that is why it is a major component of your Beyond Burger, the plant imitation of a hamburger,” he said.

James Cameron promotion

The Prairies are poised to become the pea protein capital of the world, processing companies say.

Environmentalist and Hollywood director James Cameron and his wife, Suzy Amis Cameron, have invested in an organic pea-processing plant in Saskatchewan. The French company Roquette has also announced it will build the world’s largest pea-processing facility near Portage la Prairie, Man.

On a trip to a grocery store last week, CBC News found pea protein in frozen chicken strips and deli meats.

Mary Campagna of Woodbridge, Ont., cooks most foods from scratch and is careful to scan ingredient lists because her 10-year-old daughter, Vanessa, is allergic to peanuts, most beans and peas.

Campagna recalled what happened when she brought home pepperoni to make pizza four years ago.

“Vanessa was eating a piece of pepperoni and then putting one on the pizza and suddenly her face swelled up.”

Campagna was able to track the source of the allergy back to pepperoni that contained pea protein.


Unlike nuts, pea protein is not labelled as a food allergen in Canada. It’s still too early to know how common the pea protein allergy will prove to be, Lavine said.

She wants to raise awareness of pea protein as a “relatively under-recognized” source of allergy.

“In the past, if a child has anaphylaxis to food there’s a certain short list of foods that might be able to explain it,” she said.

Now, physicians might need to widen their search of foods for “mystery anaphylaxis.”

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CBC | Health News

Software is Increasingly Complex. That Can Be Dangerous.

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Marc Andreessen has said software is eating the world. Maybe it’s not eating the world, but every day, software becomes ever more important for the functioning of the world as we know it. The complexity of that software also keeps growing, with new bugs popping up like multi-headed hydras in systems we expect to “just work” all the time.

The Apollo 11 moonshot was done with about 145,000 lines of code and a lot less computing power than your printer. Today’s Microsoft Windows contains some 50 million lines of code. A Boeing 787 runs on 7 million lines of code, but a modern car actually runs on 10-100 million lines of code. Google’s infrastructure is estimated to have 2 billion lines of code. It takes an army of programmers to build and maintain these systems, but it is increasingly harder to code and test every permutation of what machines and users might do.

All those millions of lines of code are not written overnight, nor are they rewritten for every new release of a system or product. Systems are layered over time, and complexity and “crust” creeps in. Often one of today’s mission critical systems might layer on the shiny veneer of a new mobile app, but still rely on a codebase that’s been around for 20 years.

While there is nothing inherently wrong with the above, new user interfaces and use paradigms tend to surface problems in code for which it was never architected. The new layers inherently trust the older layers underneath, which perhaps have a new modern API grafted on to existing functionality. But a security flaw or a functional flaw in the layer underneath can cause unforeseen bugs. Apple’s recent admin login bug could be an example of old crust, a testing problem, a back door that inadvertently made it into a distribution build, or all of the above, but it shows it happens even at top companies with the best reputations for quality control.

Will software soon become too complex to fix?

Modular Coding Is to Blame

Computer researcher Bret Victor, a Cal Tech graduate and former UX designer at Apple, thinks part of the complexity in today’s software is that programmers are divorced from the problem they’re working on. Most of today’s code is still based on constructs of letters and symbols. While they’re far easier to write and understand than yesterday’s assembly language and FORTRAN (going back to that Apollo timeframe), it still forces the programmer to think in terms of only their module’s interfaces and outputs, and not necessarily understanding the use case or the system it fits in. And that model, despite the aids provided by today’s sophisticated development environments (IDEs like Microsoft’s Visual Studio or the open source Eclipse), is still largely how code is developed.

In 2012, Victor’s Inventing on Principle talk at the Canadian University Software Engineering conference went viral. He discussed how programmers need to be able to better visualize what they are creating. In complex systems with millions of lines of code, it might be hard to make that immediate connection, as running a full system build is not exactly like rebuilding an iPhone app. But his point is the model of building software – not just the toolset – needs to change to ensure programmers can actually understand in real time what they’re building, and how changes they introduce affect the final product.


Machine Learning Algorithms

Machine learning and AI may well end up being what “eats the world.” Machine learning is replacing the model of coding for every possible input and outcome in a given application. It’s a game changer, because programmers are developing learning algorithms that gain knowledge from experience with vast quantities of data. In linear coding, humans are programming computers for all the situations they imagine need to be handled. In machine learning, the algorithm is training the machine to deal with situations by simply encountering as many as possible. It’s what’s enabling rapid advances in self-driving car technology, as well as deciding what Facebook posts to show you at any given moment.

But machine learning introduces yet more complexity into the mix. Neural networks are many layers deep, and the algorithm developers don’t always know exactly how they end up at a specific outcome. In a sense, it can be a black box. Programmers are inserting visualizations into neural network algorithms to better understand how the machine “learns” – it’s not unlike trying to understand the unpredictable thought patterns human brains go through in making a decision.

Sometimes, the results can be surprising. An early version of Google Photos’ image recognition algorithm was tagging some African-American faces as gorillas – which despite the racist implication, was simply an algorithm that needed tuning and perhaps a lot more experience with the nuances of certain images. In a world that leans more on machine learning algorithms than linear coding, programmers will have less absolute control over the machine. They’ll need to be more like coaches, teachers, and trainers – teaching the algorithms, like a child, about the environment they operate in and the proper behaviors in it.

Users Can’t Fix Problems Easily Anymore

As software takes over the world, we are increasingly dependent on things controlled by code. The world used to automate things with mechanical and electrical solutions, physical things we could actually see much of the time. Going back 30 years or more, it was not atypical for people to diagnose at least some simple things that might go wrong with technology. If your car stopped running, you might run through some exercises to see if it’s an alternator, a loose spark plug wire, or something else you might actually see or get to. Some cars today might shut the powertrain down completely based on a sensor detecting a potential problem or a drive-by-wire system failing – but you may have no idea what happened other than the car flashing a warning for you to call your dealer immediately. If your smartphone unexpectedly freezes, and every time you reboot it the same thing happens, do you really know how to fix it? With cloud-based software updates, and the increasingly locked down nature of devices, it’s harder for a user to figure out what’s wrong with a piece of technology they may be utterly dependent upon for communicating with family, navigating, and remembering where they were supposed to be an hour ago.

Our machines will increasingly controlled by software, not us. If that’s the case, software quality has to improve. Leslie Lamport, a computer scientist now at Microsoft Research, thinks programmers jump into coding too quickly rather than better thinking through design and architecture. He also said programmers today need to better understand the advanced math that underlies system theory and algorithms. Indeed, today’s popular Agile approach to software development may exacerbate jumping into code. Agile advocates building something in a short sprint, getting it to a user base to hammer on it and get feedback, fleshing it out, and iterating that until you have a finished product the users like. Market pressures also sometimes contribute to companies building new features into systems that millions of people might use and become dependent on, but without adequate testing or understanding the full impact of that functionality on the rest of infrastructure they ride on.

If we’re going to be so dependent on software, we’ll need to make sure we understand what it’s doing. If that software is a machine-learning algorithm, we’ll need to understand what it’s learning from and how to teach it appropriately. Ultimately, we may need better models for building tomorrow’s systems.

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