A Bounded Emotionality Perspective on the Individual in the Organization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Traditionally, books on organizational behavior proceed in a linear fashion from the individual, to groups, and then to the organization as a whole. This volume is no exception. Organizations exist only because of the people within them. Consequently, understanding organizations first of all requires understanding the people who populate them, and especially their needs, drives, and capabilities. It is all the more surprising therefore to find that organizational behavior scholars, and behavioral science researchers in general, were so slow to appreciate the centrality of emotion in organizations (see Ashforth & Humphrey, 1995). Indeed, even today, many scholars are reluctant to accept an emotions-oriented explanation of motivation and behavior (e.g., Becker, 2003). Interestingly, and as Weiss and Brief (2002) pointed out, early organizational behavior scholars were deeply interested in the role of feelings and emotion, but this research seems to have withered with the rise of behaviorism in the 1940s and 1950s.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it