Multiple Paths to Just Ends: Using Narrative Interviews and Timelines to Explore Health Equity and Homelessness
Bibliographic record
Abstract
Underlying the daily lives of people with experiences of homelessness and mental illness is a complex interplay of individual and structural factors that perpetuate cycles of inequity. The introduction of novel methodological combinations within qualitative research has the potential to advance knowledge regarding the experience of health equity by such individuals and to clarify the relationship between these experiences and broader structural inequities. To explore the lived experience of inequity, we present a thematic analysis of narrative interviews in conjunction with timelines from 31 adults experiencing homelessness and mental illness. Use of these methods together enabled a novel and expanded appreciation for the varied ways in which differential access to the social determinants of health influences the trajectories and experiences of inequity for people who are homeless and mentally ill. The further utility of these methods for better understanding the experience of inequity is explored and implications for research, policy, and practice are discussed.
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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 | 0.027 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".