Taking Workplace Decisions Seriously: This Conversation Has Been Fruitful!
Bibliographic record
Abstract
We are gratified by the large number of commentaries to our focal article (Dalal, Bonaccio, et al., 2010) that advocated greater integration of industrial–organizational psychology and organizational behavior (IOOB) with the field of judgment and decision making (JDM). The commentaries were uniformly constructive and civil. Our disagreements with the commentaries are mild and are limited primarily to the roles of external validity, internal validity, and laboratory experiments in IOOB. For the majority of our response, we attempt to build on the views expressed in the commentaries and to articulate some thoughts regarding the future. We structure our response according to the following themes: barriers to cross-fertilization between IOOB and JDM, areas of existing and potential JDM-to-IOOB cross-fertilization, areas of potential IOOB-to-JDM cross-fertilization, and ways to increase (and ideally institutionalize) cross-fertilization. We hope our focal article and our response to the commentaries will help to ignite exciting basic research and important practical applications associated with decision making in the workplace.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".