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Record W2960712775 · doi:10.11575/prism/32022

Gender Parity on Corporate Board of Directors: A Public or Private Policy Issue?

2017· dissertation· en· W2960712775 on OpenAlexaboutno aff
Amber S. Griffith

Bibliographic record

VenueOpen MIND · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsParity (physics)AccountingBusinessPolitical scienceCorporate governanceFinancePhysics

Abstract

fetched live from OpenAlex

Gender diversity on corporate board of directors is a policy concern in Canada as women's inequality has broad societal and economic implications. The strength and long-term success of Canadian public corporations depends on the highest quality board management. Significant research and reports show a positive correlation between increased diversity on boards and improved corporate governance and financial performance. Nonetheless, women currently only hold 12 percent of board appointments on publicly-traded companies in Canada and 45 percent of companies listed on the S&P/TSX still do not have any women on their boards. A number of factors have led to the slow progress of board diversification in corporate Canada. While Bill C-25 to amend the Canadian Business Corporations Act proposes disclosure rules consistent with the “comply or explain” rules of current provincial security regulators, gender parity policies must be better informed and carefully designed to ensure that women succeed in board appointments. This project was designed as a pilot project in order to determine the feasibility of government legislating gender parity on corporate board of directors in Canada. Confidential discussions were conducted with 35 informed individuals from public, private and not-for-profit sectors, including mid to top-level professionals, both male and female, from various industries and backgrounds. Qualitative data analysis involved a comparison of respondents' views expressed on government involvement in creating board diversification in corporate Canada, allowing for an in-depth understanding of the current attitude in Canada. Respondents provided insight and shared their views on the current state of affairs as well as policy initiatives including “comply or explain,” quotas, and/or private measures. Key themes from the literature review served to guide the data analysis process. Several explanatory factors have been found to contribute to the continuous low representation of women on corporate board of directors in Canada, specifically around women's life choices, mentorship and sponsorship opportunities, and multiple elements involved in the recruitment process for new board members. Findings propose that the underlying issues impacting female representation on corporate boards are complex and a strong desire to maintain the status quo hinders progress. The explanatory factors identified in this project strongly contribute to the low number of women on corporate boards. Policies involving targets or quotas will not succeed if the organizational culture and “pipeline” questions are not addressed. With organizational policies to address the number of women in leadership roles combined with stricter disclosure requirements to encourage companies to diversify and highlight progress to investors, the status quo can be altered. Moreover, a government-sponsored commission of established industry professionals should be established to coordinate with industry and drive change. Any policy approach designed to increase the number of female board directors should involve a partnership between the public and private sector.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.776
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.010
Scholarly communication0.0080.004
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.384
GPT teacher head0.422
Teacher spread0.038 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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