Relationality and Reflexivity in Community-based Research: Reflections from the Field
Bibliographic record
Abstract
Relationships, and the establishment of them, are a fundamental component of our work in community whether in service-learning settings or in conducting communitybased research. Yet, seldom do we articulate how we develop, negotiate, maintain, and manage or even understand these interactions. Reflection, a critical and necessary component underlying community-based practice, can be used to explore these aspects. In this paper we present the reflections of women who have been homeless and student researchers who were involved in a community-based research project related to women and homelessness. The reflections share their common journey of moving from uncertainty and fear to becoming increasing comfortable in the process of collaborative community-based research. This journey occurs through the creation of a shared purpose related to both individual empowerment and creating social change and social justice for other women who are marginalized by poverty and homelessness.
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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 | 0.080 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.089 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.007 | 0.020 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".