More women, more money? The impact of discourse on legal and regulatory initiatives regarding women on corporate boards
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The advancement of women on corporate boards is an oft-discussed social issue in many countries. Little existing scholarship, however, compares the nature of legal and regulatory initiatives across international jurisdictions. Similarly, although there is a plethora of research into the potential economic benefits of increasing the number of women on corporate boards, almost none of the academic literature explicitly considers the nature of the arguments used to support measures to further this goal. This thesis addresses such shortcomings by examining common threads in the arguments around gender diversity on corporate boards and applying doctrinal analysis to characterise the existing (and some proposed) legal and regulatory initiatives that have sought to address the issue. This forms the basis of an exploration of the relationship between the discourses that frame the debate regarding women on corporate boards and the various policy interventions introduced to advance that goal. The thesis uses case studies to trace the relationship between discourse and policy in four countries: Norway, Canada, the United Kingdom and Australia. Analysis of these relationships highlights the complex interplay between discourse and policy implementation and points to three significant conclusions. Firstly, the primary discourses surrounding women on boards are worth attention in their own right. Secondly, discourse affects policy. The assumptions inherent in dominant discourses can pre-emptively exclude certain policy initiatives from consideration, even causing advocates to undermine their own stated aims. Thirdly, and most encouragingly, the resulting analyses likewise suggest that policy initiatives and regulatory measures, once implemented, can impact on discourses and even public attitudes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it