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Record W4319729179 · doi:10.55482/jcim.2022.33288

The Effect of Board Gender Diversity and Environmental Responsibility on Innovation: Evidence from the Top-Patenting Firms

2022· article· en· W4319729179 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Comparative International Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDiversity (politics)TrademarkBusinessGender diversityScope (computer science)Face (sociological concept)Sample (material)Industrial organizationAccountingPolitical scienceLawFinanceSociology

Abstract

fetched live from OpenAlex

Today, firms face joint pressures to increase the representation of women at the highest levels of their organizations, and to be more environmentally responsible. Still, the impact of these movements on firm performance is less clear. Through the lens of the Attraction-Selection-Attrition (ASA) Cycle, this study looks at the impact of Board Gender Diversity (BGD) and Environmental Responsibility on Innovative Output as measured by patents. Using a longitudinal sample of the top-patenting firms at the United States Patent and Trademark Office, we find that both BGD and Environmental Responsibility lead to higher levels of Innovative Output, and BGD positively moderates the relationship between Environmental Responsibility and Innovative Output. This paper contributes to existing literature by highlighting the need to consider BGD and Environmental Responsibility at the same time when considering their implications on firm performance. We also expand the scope of the ASA Cycle to include overall firm performance with respect to innovation.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.010
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.003
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 head0.036
GPT teacher head0.268
Teacher spread0.233 · 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