Patients, consumers and civil society
Bibliographic record
Abstract
Citation (2008), "Patients, consumers and civil society", Chambré, S.M. and Goldner, M. (Ed.) Patients, Consumers and Civil Society (Advances in Medical Sociology, Vol. 10), Emerald Group Publishing Limited, Bingley, p. iii. https://doi.org/10.1016/S1057-6290(08)10017-1 Publisher: Emerald Group Publishing Limited Copyright © 2008, Emerald Group Publishing Limited Book Chapters Advances in medical sociology Patients, consumers and civil society Copyright page List of contributors Introduction No longer a patient: The social construction of the medical consumer Direct to consumer responsibility: Medical neoliberalism in pharmaceutical advertising and drug development Making connections: Egg donation, the Internet, and the new reproductive technology marketplace Selling the ideal birth: Rationalization and re-enchantment in the marketing of maternity care Too Posh To Push? Comparative perspectives on maternal request caesarean sections in Canada, the US, the UK and Finland Self-help groups challenge health care systems in the US and UK From discovery to recovery and beyond: The role of voluntary health sector organizations in the lives of women with breast cancer The clubhouse model: Mental health consumer–provider partnerships for recovery Straight from the heart Speaking for stem cells: Biomedical activism and emerging forms of patienthood Forging a new commons: Self-help associations in Slovenia and Croatia Gendered networks and health care privatization
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".