Does Ethical Reinforcement Pay? Evidence from the Canadian Mutual Fund Industry in the Post‐Financial Crisis Era
Bibliographic record
Abstract
Abstract This study elucidates the link and effect of ethical reinforcement in the post‐financial crisis era by taking two congruent directions to demonstrate that ethical reinforcement can be accomplished by either a continuous ethical training or a meticulous code of business ethics—which members of the mutual fund industry claim they adhere to—as both have a positive effect on the funds’ performance, including sizeable gains to investors. Furthermore, evidence divulges that ethical reinforcement moderates the performance of ethical or socially responsible investments (SRI) funds more than nonethical investments, suggesting that a perspective of ethical or SRI classification of a fund alone is not sufficient , but it is necessary to have the institutional ethical environment and/or managers’ continuous ethical training. This result supports the notion of financial market discipline and reveals some factors behind SRI or ethical funds returns, notably during the period following the recent financial crisis.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".