Adaptation of Consultation Planning for Native American and Latina Women With Breast Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Resource centers in rural, underserved areas are implementing Consultation Planning (CP) to help women with breast cancer create a question list before a doctor visit. PURPOSE: To identify changes needed for acceptable delivery of CP to rural Native Americans and Latinas. METHODS: We interviewed and surveyed 27 Native American and Latino key informants. We coded interviews thematically, and calculated summary statistics for the survey data. FINDINGS: Native American and Latino respondents endorsed CP as culturally acceptable to their communities, while suggesting changes. Respondents also raised the topic of how to further support patients once they have successfully prepared a question list using CP. CONCLUSIONS: The resource centers implemented the requested changes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it