The entrepreneurship of survival among urban adults experiencing homelessness and mental illness
Bibliographic record
Abstract
AIMS: Using an entrepreneurship lens, this study examined the narratives of urban adults experiencing homelessness and living with mental illness, to explore strategies used for day-to-day survival. METHODS: Semi-structured qualitative interviews were conducted with 14 females, 30 males, and one individual identifying as "other," living in a mid-sized Canadian city. The average age was 39 years. Data were transcribed verbatim and analyzed using thematic analysis informed by grounded theory. FINDINGS: Participants described creative and intentional strategies for managing life on the street without permanent shelter, including recognition of opportunities, mobilization of their own or acquired resources, and use of social connections and communication skills, and strategies that demonstrated entrepreneurial processes. CONCLUSIONS: Findings suggest that participants used survival entrepreneurship strategies and processes to navigate daily life while experiencing homelessness. Recognition and validation of the propensity for enterprise and self-sufficiency are central for both individual recovery and ending homelessness within similar populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".