A Narrative Ethnography of Mothering and Motels: Mothers Experiencing Homelessness in Ontario and Bureaucratic Abandonment
Bibliographic record
Abstract
This is a narrative ethnography about the concepts of “care,” “mothering” and “homelessness” in our current neoliberal context. “Care” is to be understood as both State Care, but also care in terms of the positionality and construct of what it means to do “mothering,” particularly when under the specific bureaucratic constraints and regulations imposed by the Ontario welfare state while experiencing homelessness. A historical analysis of families experiencing homelessness (particularly mothers) post-1995 in Ontario enables situating the housing crisis (especially in Toronto) within the shifting neoliberal policies of merit/risk assessment that have infiltrated welfare states globally — transitioning the accessing of welfare services and resources from a use-value to exchange-value paradigm. Instead of focusing attention on the immediate material needs of mothers experiencing homelessness in Ontario, the focus becomes one of bureaucratic risk assessment consistent with the neoliberal economic ethos of futurity. Mothers are categorized and assessed for various levels of potential future risk leading to a negation and disappearance of the current realities of these women’s lives, disenabling the meeting of their actual needs both immediate and long-term. My primary argument throughout this dissertation is that the narratives of mothers experiencing homelessness in Ontario be placed within the larger framework of neoliberalism. The localized experiences of the mothers I spoke to are part of the globalized terrain of precarity, migration, job loss, and housing affordability. Although unique, their stories are also part of this larger tapestry of disenfranchised populations struggling to find housing stability for themselves and their families. I hope my writing can help enhance empathy, understanding and tolerance.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.014 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".