Agency costs of multiple directorships: Toronto Stock Exchange - 2007-2008
Bibliographic record
Abstract
This paper is a treatment of the agency costs to shareholders potentially caused by multiple directorships in firms listed on the Toronto Stock Exchange. The sample set is comprised of the compulsory annual reports as extracted from the OSIRIS database service by Bureau van Dijk Electronic Publishing. The data is limited to partial annual reports for 2007 and 2008 in order to capture the collapse in the financial sector in the United States. A score ofworkload is assigned to over 14,000 reported director positions. The position data is then tallied and cross-referenced to produce information on board workload within a firm and the total workload those directors face. The governance score, the difference between those workloads, is intended to capture director workload external to the board. This is compared to a definition of agency cost using a log regression. Weakness in the initial results created a desire to apply another analytical tool -a comparison of averages using EViews. There appear to be effects of underconnected and over-connected boards of directors but the definition of agency cost seems to be insufficient.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".