The Impact of Industry-level Downsizing Prevalence on Organization-Level Layoff Implementation
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
This research examines the impact of downsizing prevalence among referent firms in the industry on organizational downsizing activity. The study posits that organizations operating in industries with high downsizing prevalence assume a cost-containment approach, while organizations operating in industries with low downsizing prevalence draw upon social exchange theory when operationalizing layoffs. Accordingly, organization-level layoff implementation considerations (i.e. severity, frequency, alternatives, explanations, and advanced notice) for organizations operating in high versus low downsizing prevalence are compared, using a comprehensive population of all mass layoffs events in Ontario, Canada from March 2013 to May 2019 (n=418). The findings identify that the industry level downsizing prevalence impacts the layoff severity, use of alternatives and types of explanations provided.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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