Corporate governance reforms: profiling at its worst
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
Purpose Looks at modern guidelines for corporate governance as essentially an exercise in profiling. Sarbanes‐Oxley, oversight agencies, and self‐regulatory agencies focus on the adoption of certain board composition configurations in a purely subjective way and on the basis of factors not clearly linked to outcomes. This paper suggests that other behaviors can more accurately measure performance. Design/methodology/approach Delineates the more salient behaviors and activities that inform whether boards are effectively meeting their responsibilities. Findings The following characteristics are more predictive of board performance than those presently used: having an independent board budget; appointing lead independent directors; including emeritus directors; not including a retired CEO on the board; executive sessions for independent board members; elimination of executive committees; refraining from related party transactions. Practical implications Provides managers with information on important factors to consider when selecting, measuring and evaluating boards of directors. Originality/value Of particular value to CEOs and other board members.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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