Moving Toward Understanding: Negotiating Survival and Wellbeing while Living in Poverty
Bibliographic record
Abstract
Poverty in Canada continues to be regarded as an individual problem, rather than a set of complex and institutional systemic failures. Moreover, there remains a longstanding and problematic belief that poverty, homelessness, and disenfranchisement can be ‘solved’ by those living in precarity by merely working harder, and that individuals remain in poverty because of their own independent choices and decisions. This is evidenced through dominant neoliberal discourses surrounding personal responsibilities which will be addressed in this dissertation. What these discourses have failed to address are the frameworks, contexts, and spaces within which poverty is structurally and systemically reproduced. Individuals and communities do not stumble upon poverty. Classism, colonialism, racism, homophobia, ableism, and marginalization, which are visible through poverty, lend themselves to the perpetuation of poverty across generations, as well as purposefully disenfranchising particular intersections of people. What endures then, is a both lack of understanding and wilful neglect about the lived experiences of poverty and homelessness, existing realities of risk, how cycles of poverty become reinforced through relational, institutional, and systemic means, and the role that physical activity and movement has on the lives of the poor. In this dissertation, I interrogate how macro level power structures impact the everyday, micro level lives of people experiencing poverty and homelessness. The data collected in this work comes from a nine-month institutional ethnography at Start Me Up Niagara (SMUN), in St. Catharines, Ontario Canada, where I observed, gathered field notes, and conducted interviews with staff and people who used SMUN. In my findings, I explore how individuals navigate health and wellbeing while experiencing poverty. I address the (in)accessibility to public and private spaces and emphasize the important role of care providers in space of care, like SMUN. I highlight throughout my findings how individuals in Canada experiencing poverty and homelessness, fundamentally, suffer from a lack of health justice, spatial justice, and justice of care. This work addresses the goal of eradicating cycles of poverty and injustice in Canada by highlighting the need for policy implementations at all levels of government. Ethical approval was received by the University of Toronto Research Ethics Board (protocol# 35175).
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.035 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".