Emotional and Interpersonal Dimensions of Health Services
Bibliographic record
Abstract
Contributors examine the degree to which the provision of health care is influenced by characteristics of the health service organization, such as the administrative structure and the human resources available. They demonstrate that job satisfaction and conditions play an important role in shaping the quality and effectiveness of care and discuss the emotional support health care providers need to avoid long-term exhaustion and ensure well being. The contributors identify qualities of the client-provider interaction that lead to positive health care outcomes, such as providing information, responding to patient concerns, facilitating interactions with the health care system, and encouraging participation in personal health care and offer examples of innovative conceptual and analytical approaches to better health care practices. Contributors include Heather Boon (University of Toronto), Laurette Dubé, Carole A. Estabrooks (University of Alberta), Guylaine Ferland, Arlie Russell Hochschild (University of California, Berkley), Diane M. Irvine Doran (University of Toronto), Terrence Montague (Merck Frosst Canada), D.S. Moskowitz, Richard W.J. Neufeld (University of Western Ontario), Gilbert Pinard (McGill University), Debra L. Roter (John Hopkins Blooomberg School of Public Health), Dana Gelb Safran (New England Medical Center), and Krista K. Trobst (York University).
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".