Bibliographic record
Abstract
There is a growing acknowledgement that organizations comprise a plurality of concerns and interests. Among community-based organizations, such plurality has been studied as so many tensions that impede work and that must be resolved. In contrast to such a view, we adopt the posture that the multiplicity of voices is something that organizational members, as individuals, actively and reflexively enact. Our study looks at such enactment in the context of the Women's Health Project, a community-based participatory research project focused on health promotion in a racially and ethnically diverse urban population center. More specifically, we study how peer health advocates (i.e., women from the district hired and trained to disseminate health information to their fellow residents) utter multiples voices (including by a single person) and interactionally manage them. We then observe the organizing effects that stem from three processes they enact: deploying alternative identities, transposing practices, and melding voices. We conclude by noting how these processes allow the peers to discursively bridge between the world of the clinic and their neighbourhood world and enable the Project to balance cultural competency with fidelity to health information.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.088 | 0.010 |
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; both teacher heads agree on what is shown here.
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".