Not just ‘for’ but ‘with’: health advocacy as a partnership process
Bibliographic record
Abstract
CONTEXT: Health advocacy is often framed as an activity that physicians do for others. A physician uses her expertise to identify and address the health needs of patients or communities on their behalves. As part of a larger study, we uncovered data to suggest that effective health advocates work not just for but often with others to understand and address their health needs. OBJECTIVES: This paper explores and elaborates the important distinction between advocating with and for others. METHODS: We interviewed 10 physicians, identified by others as successful health advocates, about their advocacy activities. Informed by constructivist grounded theory, we gathered and evaluated data iteratively, continually revising the interview outline and concurrently refining our evolving themes. Once it had stabilised, the coding scheme was applied to the full set of transcripts. RESULTS: Health advocacy was framed by participants as an activity that was more often done with others, than for others. This manifested in two ways: (i) joining other voices: rather than always feeling a need to plan and act alone, our participants often described making efforts to find and join existing initiatives and to work collaboratively, and (ii) amplifying other voices: rather than authoritatively determining needs and enacting solutions on behalf of others, our participants often described making efforts to empower others to find their own voices, thereby fostering autonomy rather than reliance. Participants described factors and mechanisms that enabled them to approach advocacy in this manner. CONCLUSIONS: Successful health advocates often enact health advocacy with others, rather than exclusively for them. This partnership-based facilitative approach enables them to better appreciate the needs of those requiring support, and to ask: 'How can I help?' If this approach were more effectively reflected in formal constructions of the process, health advocacy might not only be practised more effectively, but might also be perceived as more achievable by trainees and physicians.
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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 | 0.067 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.030 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".