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 This study shows that contrary to what many managers argue, there is no overreaction to earnings warnings. Our sample consists of 986 firms that had significantly lower fourth‐quarter earnings than analysts' forecasts during the period of 1983 to 1998. About 9% of these firms released quantitative earnings information while 6.5% of the firms disclosed qualitative earnings information prior to the formal earnings report dates. We find that although these firms experience significant stock price declines during the warning period, their share prices are still higher than the economic values, calculated using Ohlson's residual income model. Further, long‐run operating and stock performance of these firms are not more positive than the performance of firms that do not warn. We also find that investor reaction to both warning and non‐warning firms is positively related to the firms' long‐run stock and operating performance. These findings support the argument that investors do not overreact to the warnings but base their reaction on anticipated long‐term performance of the firms.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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