Compensation practices and determinants of CEO pay: The case of Ontario not-for-profit hospitals
Bibliographic record
Abstract
Two interpretations are possible. Ontario hospital boards may be trading-off the difficulties in implementing a formal pay-for-performance incentive plan with a more subjective and comprehensive evaluation process. This supports the claim that monitoring and bonus plans can both be used as an executive motivational device. Another interpretation, a criticism expressed in current business literature, is that agency problems are unaddressed in current CEO contracting arrangements, and the use of peer comparison and competitive benchmarking simply ratchets up year-to-year CEO compensation. Corporate governance entails monitoring, evaluating and rewarding the performance of the Chief Executive Officer (CEO) of the corporation. An economic approach to understanding CEO compensation predicts that financial incentives will be written into the CEO's compensation contract to align the goals of the owners of the firm with those of the top executive of the firm. At the same time, economic theory predicts that not-for-profit organizations, which have multiple stakeholders, complex multidimensional missions and hard to observe and measure outputs, may be unable to write similar incentive contracts for the CEO and hence suffer from enhanced agency problems. This thesis is an exploratory investigation into the CEO compensation policies employed by the Board of Directors of Ontario public not-for-profit hospitals. A survey of CEOs and boards finds that the majority of Ontario hospitals do base CEO compensation in part on performance, this performance evaluation being a comprehensive review of CEO specific performance goals and objectives, including specific hospital targets. These surveys also highlighted that Ontario hospital boards have had difficulties in establishing formal pay-for-performance systems due in large part to hospital outcomes being perceived as largely beyond the control of the CEO. Guided by equity theory, an empirical model investigates how pay comparisons with peer hospital CEOs influence subsequent CEO compensation adjustments, and finds that changes in CEO compensation are significantly related to the relative inequity position of a CEO compared to its peers.
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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 | 0.005 | 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 | 0.000 |
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".