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
We investigate the effects of the data breach notification (DBN) mandate in the U.S. on firms’ selling, general, and administrative (SG&A) cost behavior. We find that firms affected by these laws show reduced SG&A cost stickiness. This reduction is attributed to diminishing managerial optimism about future sales following the implementation of DBN laws, arising from an anticipated increase in the disclosure of data breaches, which leads to more pronounced cost reductions when sales decline. Additionally, firms with higher adjustment costs, greater breach likelihood, and lower liquidity experience more pronounced effects. Finally, we document improved operating efficiency, accompanied by lower future capital expenditures, for firms with reduced cost stickiness following the DBN. These findings contribute to cost management and data breach literature by demonstrating how DBN laws reshape managerial behavior, improving cost structures and operational efficiency.
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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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