WHEN THE BORED BEHAVE BADLY: AN INTEREST ENHANCEMENT MODEL OF COUNTERPRODUCTIVE WORK BEHAVIOR
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
How do beer bottlers in a droning brewery cope with boredom on the job? Do they have imaginary conversations with beer cans? Do they make obscene objects out of packaging glue? Perhaps they fantasize about throwing the bottles like grenades while contemplating the ensuing explosion. Indeed, Molstad (1986) documented instances of all three in his ethnographic study of industrial brewery workers. Boredom is a frequent experience of working life and individuals must find ways to cope with the state. I contend that employees often manage boredom by actively creating interest or stimulation in the task, activity, or work environment. At times, these interest enhancing behaviors may negatively affect job performance and run counter to the goals of the organization.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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