Aprendiendo a Trabajar en Colaboración con Mujeres de Bajos Ingresos Económicos en la Ciudad de Kingston, Ontario, Canadá: Reflexiones sobre un Proyecto de Investigación Acción Participativa
Bibliographic record
Abstract
This paper presents our experience following participatory methodologies to understand the experience of access to health and social services for women living on low-income in Kingston, Ontario, Canada. Goals: The study aims are to describe and understand our experiences implementing a PAR study. Methods: In this study, we use participatory (PAR), art-based research (photovoice), and interpretive (hermeneutic phenomenological) approaches. Results: In this paper, we report our processes and experiences to date doing PAR with a not-for-profit organization in Kingston, Canada, both the challenges and the rewards, but most importantly the necessity of it for this context. This work has included the need to be adaptable and creative in light of COVID-19 restrictions, particularly while still striving to maintain study momentum. Conclusion: We have learned that a PAR study needs time, commitment and motivation. For meaningful, sustained change it must be enabled through partnership – one that honors and benefits those most in need.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.043 | 0.023 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.009 |
| 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".