Homeless youth‐led activism and direct action: Lessons from a participatory research project in Tio'tia:ke/Montréal
Bibliographic record
Abstract
Abstract This article explores the involvement of youth with lived experience (LE) in activism and research aimed at addressing youth homelessness in Canada. Based within a youth‐participatory action research project in Tio'tiá:ke/Montréal, Canada, we reflect on how young people described their own activist organising, as well as the practical ways we may harness actions that homelessness youth are already doing to create communities and solidarity. The authors are members of Youth Action Research Revolution (YARR), a research team primarily made up of youth with LE of homelessness. We position the analysis at an intersection of our own experiences and 63 interviews with youth aged 16–29 conducted by YARR from 2018 to 2021. Conceiving of participatory, youth‐led research as a form of direct action we outline lessons learned from our own research and LE. Young people within our team and participants in YARR's research shared critiques of State systems while outlining the work that they undertook with their peers to act on issues of housing precarity, often eschewing activism aimed at State processes or institutional reform in favour of direct action. This article proposes a mode of fostering youth‐led, socially just change around homelessness—one that shifts conversations from inclusion to solidarity, and recognises the radical potential of research by‐and‐for young people. The authors conclude that research and advocacy on homelessness is always inherently political for young people with LE, and that harnessing the direct action that youth already do to survive is not only a socially just form of mobilising, but can contribute to broader activism towards housing justice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.032 | 0.023 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".