What questions do board members in public service organizations ask about executive compensation?
Bibliographic record
Abstract
The purpose of this study is to investigate the governance questions that board members in public service organizations ask as they go about fulfilling their responsibilities for the oversight of executive compensation. The research uses 24 of the questions – as proposed by the Canadian Institute of Chartered Accountants - that directors should ask about executive compensation and investigates both their usage and perceived importance by board members. The study is based on a usable sample of 47 board members from public service organizations who were attending a Canadian director training program. The research finds that, insofar as public service organizations are concerned, not all of the recommended executive compensation governance questions were asked with the same frequency nor were they considered equally important. Additionally, the relationship between a question’s usage frequency and its perceived importance was not perfect. However, there appears to be a significantly positive relationship among the number of executive compensation governance questions asked and selected elements of a board’s governance structure.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".