Research in Organizational Change and Development: Reflexive Conversations of ROCD 30 Authors
Bibliographic record
Abstract
For the past 36 years, ROCD has provided the organization development and change community with a platform to share new empirical research, insights about change and organization development, and learnings relevant to scholar-practitioners. Most of the contributors to ROCD 30 (six out of seven chapters) have been in the field for 30 years or longer. As a component of celebrating the publication of ROCD Volume 30, we invited the authors to reflect on their contributions and participate in a facilitated reflexive conversation about the development of their individual and shared scholarship, on the state of the field, and on “Putting the Worker Front and Center”. Following the success in previous years, the interactive design of the session will maximize continuous conversations in small groups and in the larger community. Reflections: Individually and Jointly Reconceiving OD to Foster a Hospitable Future Author: Susan A. Mohrman; U. of Southern California, retired Author: Jean M. Bartunek; Boston College Research in OD&C: A Personal Journey through Methods and, Finally, Pragmatism Author: Philip H. Mirvis; Babson Social Innovation Lab Creating and Building Shared Scholarship in Organization Development and Change: A Metalogue Author: David Coghlan; U. of Dublin, Trinity College Author: A.B. Rami Shani; California Polytechnic State U. Applying Management and Organization Theory to Org Change & Development: More than Meets the Eye Author: Thomas G. Cummings; U. of Southern California Author: Chris Worley; Pepperdine Graziadio Business School Developing a Sustainable High Commitment, High Performance System of Organizing, Managing, & Leading Author: Michael Beer; Harvard Business School The Role and Relevance of Discourse and Discursive Perspectives in Org Change & Development Author: Clifford Oswick; City U. London Author: Yuan Li; Saint Mary's College of California Exploring the Richness of Action Learning Research to Exploit Action Learning in Networks Author: David Coghlan; U. of Dublin, Trinity College Author: Paul Coughlan; U. of Dublin
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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 | 0.066 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.017 | 0.023 |
| Scholarly communication | 0.024 | 0.015 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.006 | 0.034 |
| Insufficient payload (model declined to judge) | 0.003 | 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".