Bibliographic record
Abstract
Citation (2014), "List of Contributors", Reconfiguring the Ecosystem for Sustainable Healthcare (Organizing for Sustainable Effectiveness, Vol. 4), Emerald Group Publishing Limited, Bingley, pp. vii-viii. https://doi.org/10.1108/S2045-060520140000004002 Publisher: Emerald Group Publishing Limited Copyright © 2014 Emerald Group Publishing Limited Nils Conradi Regional Cancer Centre West, Sahlgrenska University Hospital, Gothenburg, Sweden François Dionne Vancouver Coastal Health Research Institute, Vancouver, BC, Canada, and Prioritize Consulting Ltd., Vancouver, BC, Canada Bill Doolin Auckland University of Technology, Auckland, New Zealand Andrew W. Hamer Nelson Hospital and New Zealand Cardiac Network, Nelson, New Zealand Andreas Hellström Chalmers University of Technology, Gothenburg, Sweden Tony Huzzard Chalmers University of Technology, Gothenburg, Sweden Michael Kanter Southern California Permanente Medical Group, Pasadena, CA, USA Emanuele Lettieri Politecnico di Milano, Milano, Italy Svante Lifvergren Chalmers University of Technology, Gothenburg, Sweden Terry L. Martinson Fairview Medical Group, Minneapolis, MN, USA Cristina Masella Politecnico di Milano, Milano, Italy Craig Mitton Centre for Clinical Epidemiology and Evaluation, University of British Columbia, Research Pavilion, Vancouver, BC, Canada, and Vancouver Coastal Health Research Institute, Vancouver, BC, Canada, and Prioritize Consulting Ltd., Vancouver, BC, Canada Susan Albers Mohrman Center for Effective Organizations, Marshall School of Business, University of Southern California, Los Angeles, CA, USA Giovanni Radaelli Politecnico di Milano, Milano, Italy Diane Schmidt Prioritize Consulting Ltd., Vancouver, BC, Canada Abraham B. (Rami) Shani Orfalea College of Business, California Polytechnic State University, San Luis Obispo, CA, USA, and Politecnico di Milano, Milan, Italy Michele Tringali Lombardy Region General Health Directorate, Milano, Italy Stuart Winby Spring Networks, Palo Alto, CA, USA Christopher G. Worley Center for Effective Organizations, Marshall School of Business, University of Southern California, Los Angeles, CA, USA Book Chapters Reconfiguring the Ecosystem for Sustainable Healthcare Organizing for Sustainable Effectiveness Reconfiguring the Ecosystem for Sustainable Healthcare Copyright Page List of Contributors Reconfiguring the Ecosystem for Sustainable Healthcare: Introduction to the Volume Acknowledgements Chapter 1 Healthcare: An Ecosystem in Transition Chapter 2 The Design and Acceleration of Healthcare Reform/ACOs: The Fairview Medical Group Case Chapter 3 Network-Based Transformation of Cardiac Care in New Zealand Chapter 4 A Physician-Led, Learning-Driven Approach to Regional Development of 23 Cancer Pathways in Sweden Chapter 5 Creating High-Value, Sustainable Healthcare: The Technical and Social Elements of Evidence-Based Medicine at the Southern California Permanente Medical Group Chapter 6 Embedding Sustainable-Effectiveness in Decision-Making within an Ecosystem: Lessons from the Health Technology Assessment Program at the Lombardy Region, Italy Chapter 7 Difficult Decisions in Times of Constraint: Criteria-Based Resource Allocation Chapter 8 Reconfiguring the Ecosystem for Sustainable Healthcare: Integrating Outside-In and Inside-Out Perspectives About the Contributors
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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 | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.712 | 0.702 |
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".