Stock investors' reaction to layoff announcements: A meta‐analysis
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
Abstract Does a firm's layoff announcement elicit a negative or a positive reaction from its stock investors? The extant empirical evidence on this question is mixed. The authors' meta‐analysis of 34,594 layoff announcements taken from 126 samples featured in 78 studies reports that the average investor reaction is significantly negative (effect size of −0.549). Next, the authors use signaling theory—specifically, characteristics of the signal, the signaler, and the signaling environment—to examine variation in investor reaction. They find that investors do not react if a layoff announcement signals proactive management (e.g., cost cutting) but penalize the firm if the layoff indicates reactive management (e.g., decline in demand). The penalty is also positively associated with layoff size but unrelated to firm size. Further, investors have become less punitive over time, or if its stock is traded on an exchange in civil law (vs. common law) country. The empirical generalizations guide managers on the consequences of their layoff announcements.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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