The Role of Gender Equality at the Country Level on the Relationship Between Women’s Board Representation and Sustainability Assurance Adoption
Bibliographic record
Abstract
Purpose: The purpose of this study is to investigate the role of gender equality in the relationship between the critical mass of women’s representation on boards and companies’ decisions to adopt external assurance on their sustainability reports. Design and methodology: The relationship is investigated using secondary data from an international sample of 1924 firms across 41 countries sourced from the Eikon database, ensuring comprehensive coverage of firms that publish sustainability reports. The study uses a logistic regression model to study two aspects: first, the relationship between the critical mass of women’s representation on boards and companies’ decisions to provide external assurance on their sustainability reports, and second, the moderating role of countries’ gender equality policies using the World Bank’s Women, Business and the Law (WBL) index. Findings: The findings of this study indicate that in the case of sustainability assurance adoption, the critical mass of women’s representation on boards is important in countries where the gender equality index is low. Therefore, this study extends the findings of prior studies investigating the critical mass of women’s representation on boards by proving that critical mass is more effective in countries that have a lower gender equality index. Originality: The two main contributions of this study are the findings that (i) the association of women’s representation on boards with companies’ decisions to provide assurance over their sustainability reports is affected by critical mass, and (ii) the critical mass of women’s representation on boards is essential in countries that have a lower gender equality index.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".