The Influence of Women on Boards on Companies’ ESG and Financial Performance in Canada
Bibliographic record
Abstract
The contemporary world requires active economic engagement of all members ofthe \nsociety so the participation of women, as half of society, seems necessary. In recent \ndecades, the rate of gender differences in labor participation have been narrowing \nsubstantially and in developed countries especially, we observe on increasing \nnumbers of women reaching top positions in different fields of work.\nIn this study, we analyze whether female on boards in public Canadian companies \nhave any significant effect on ESG and financial performance in different businesses. \nThus, the aim of the research is to examine the relationship between gender \nmanagement diversity, ESG score, and firm financial performance in public \nCanadian companies. For collecting the data, we considered the list of companies \nfrom Canadian public companies. We selected our companies based on their gender \ndiversity which have both genders in the top managers. The total panel data is \ncomposed of 398 Canadian public companies in 2019.\nThe result of our study indicates there is a positive significant correlation between \nESG score and Female on Boards. The financial part also illustrates a statistically \nsignificant relationship between women on boards and firm financial performance. \nThus, we accept H1 which women on boards in publicly listed firms in Canada are \nassociated positively with firm financial performance and ESG score.\nKeywords: ESG, ROA, women on boards, financial performance
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".