Bibliographic record
Abstract
The chapters in this volume are drawn from the best contributions to the 2008 International Conference on Emotion and Organizational Life held in Fontainebleau, France. (This bi-annual conference has come to be known as the “Emonet” conference, after the listserv of members). In addition, these referee-selected conference papers were complemented by additional, invited chapters. This volume contains six chapters selected from conference contributions for their quality, interest, and appropriateness to the theme of this volume, as well as seven invited chapters. We again acknowledge in particular the assistance of the conference paper reviewers (see appendix). In the year of publication of this volume, the 2010 Emonet conference will be held in Montreal, Canada, in conjunction with the annual meeting of the Academy of Management, and will be followed by Volumes 7 and 8 of Research on Emotions in Organizations. Readers interested in learning more about the conferences or the Emonet list should check the Emonet website http://www.emotionsnet.org.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.020 |
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; both teacher heads agree on what is shown here.
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".