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Record W4239177255 · doi:10.1504/ijcg.2018.090609

Impact of the presence of women on public sector and private corporations in Quebec: what may be learned from the multiple discourses of board members?

2018· article· en· W4239177255 on OpenAlexaffabout
Sophie Brière, Natalie Rinfret, Hélène Lee Gosselin, Maude Villeneuve

Bibliographic record

VenueInternational Journal of Corporate Governance · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPerspective (graphical)Diversity (politics)Competence (human resources)Corporate governanceQualitative researchGender diversityDiscourse analysisPublic relationsRelevance (law)Political scienceGender studiesSociologyBusinessPsychologySocial psychologySocial scienceLinguistics

Abstract

fetched live from OpenAlex

This study presents a qualitative research conducted with boards of directors in large organisations from various sectors of the Quebec economy. From a critical perspective, this research documents element related to the perceived impact of the presence of women on boards through the members discourse and the boards practices. The results show that the two types of discourse mentioned in the literature – competence and individual gendered - are present among board members. The results reveal the presence of a discourse on diversity distinct from the other two. Perceived as a catalyst for change, that discourse attaches importance to the significant impact of mixing men and women. However, in the respondents diversity discourse, few tangible changes in gender dynamic within boards are observed. This study highlights the relevance of examining the presence and impact of women on boards from a new angle with a perspective that goes beyond statistical data and multiple discourses.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.127
GPT teacher head0.326
Teacher spread0.199 · 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 teacher head, 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
Published2018
Admission routes2
Has abstractyes

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