MétaCan
Menu
← Back to cohort
Record W4200490339 · doi:10.3390/jrfm14120596

The Relationship between LGBT Executives and Firms’ Value and Financial Performance

2021· article· en· W4200490339 on OpenAlexvenueno aff
Isabel Lourenço, Donatella Di Marco, Manuel Castelo Branco, Ana Lopes, Raquel Wille Sarquis, Mark T. Soliman

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsGoodwillValue (mathematics)BusinessEnterprise valueHuman capitalMarketingFinanceEconomicsMarket economy

Abstract

fetched live from OpenAlex

Drawing on resource-based theory, we analyze the relationship between having LGBT executives in a firm’s leadership positions and its value and financial performance. The existence of LGBT executives is considered to be associated with employee and customer goodwill towards LGBT-friendly policies and practices and to lead to human capital and reputational benefits. Our findings suggest that there is a positive effect of the presence of LBGT executives on a firm’s value, both directly and indirectly, through its effect on the firm’s financial performance. We interpret this as suggesting that besides the direct effect of the existence of LGBT executives on a firm’s value, an indirect effect also exists, mediated through financial performance, presumably through the effect that this has on employee and customer goodwill towards LGBT-friendly policies and practices. As far as we are aware, our study is the first to examine the impacts of the presence of LGBT executives, as well as distinguish between its direct and indirect effects on firm value.

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)0.001
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.208
Teacher spread0.192 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of risk and financial management→Same topicCorporate Finance and Governance→French-language works237,207→