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Record W3177162760 · doi:10.22495/cocv18i4art1

Diversity on corporate boards: A systematic review

2021· review· en· W3177162760 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCorporate Ownership and Control · 2021
Typereview
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsOperationalizationDiversity (politics)Framing (construction)Perspective (graphical)Agency (philosophy)SociologySystematic reviewPublic relationsPolitical sciencePositive economicsSocial scienceEpistemologyEconomicsComputer scienceGeographyLaw

Abstract

fetched live from OpenAlex

This study conducts a systematic review and provides a comprehensive up-to-date review of the literature about diversity on corporate boards. Unlike previous studies, we do not restrict our search to a specific type of diversity (e.g., gender diversity) or limited firm outcomes (e.g., firm performance). Our aim is to review, evaluate, synthesize, and summarize the literature and extend our knowledge on five key areas: 1) the theoretical approach (going beyond the theoretical analysis of each article by exploring how the theoretical perspective informs their focus); 2) dominant framing and theorizing (single theory vs multi-theories); 3) determinants and consequences; 4) how board diversity is defined and operationalized; and 5) the outcomes of board diversity. In reviewing the research from 2010 to February 2021 and using Saint Mary’s University Business Source Premier (SMU EBSCO) database, we identify 46 articles. Our findings reveal that agency theory no longer dominates board diversity research and has given way to institutional theory. The increasing use of institutional theory, which considers the effect of social structure on organizational outcomes, may be caused by most of the literature (based on our findings) using cross-country data. At the same time, there is a tendency to use a more multi-theoretical approach rather than a single theory one, and there are methodological limitations, including a paucity of rich data collection methods (e.g., surveys, questionnaires, and interviews). In addition, the current literature, according to the findings, focuses more on the consequences than the determinants of board diversity. Finally, our study intends to highlight and outline crucial research gaps that invite future investigation

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.337
GPT teacher head0.333
Teacher spread0.004 · 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