Connecting the Micro and Macro Approaches: Cultural Stakes in Health Communication
Bibliographic record
Abstract
Prior to the establishment of Health Communication as an independent field of study, the socio-cultural dimensions of health and illness (patient/health aide relationship, social representations in health, etc.) were largely covered by sociology and anthropology. (Adam, and Herzlich 1994) Jodelet: “These pioneering disciplines have not failed to integrate a perspective of the individual in their approach, while establishing him in his social and cultural enrolment horizon, or in the framework of his relationship with medical institutions and professionals. ” (2006:1; our translation) However, the recognition of culture in the medical field has already been formulated in 1986 during the Congress of the World Health Organization in Ottawa, Canada. A new health system trend was then defined: the promotion of health that would offer, in addition to clinical and curative services, the recognition and respect of cultural needs. Nonetheless, Jodelet (2006) puts forth the statement that psychology of health was blinded by the game of collective dimensions that intervenes in the individual and public managing of health and illness. Within these dimensions, Jodelet considers culture being almost nonexistent, despite it being a central part of several works in sociology, history, and anthropology, which were concerned with illness and health.
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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 | 0.022 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.052 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".