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Record W2123170972 · doi:10.1002/hrm.20343

Do openness to experience and recognizing opportunities have the same genetic source?

2010· article· en· W2123170972 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

VenueHuman Resource Management · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsSt. Thomas HospitalWestern University
Fundersnot available
KeywordsOpenness to experienceAffect (linguistics)Selection (genetic algorithm)HeritabilityResource (disambiguation)Bivariate analysisSample (material)BusinessMarketingPsychologySocial psychologyComputer scienceBiologyEvolutionary biology

Abstract

fetched live from OpenAlex

Abstract Recognizing opportunities for new businesses is an important part of the entrepreneurial process, one that researchers seek to explain and human resource managers seek to encourage. In this study, we examined whether the same genetic factors that affect openness to experience also influence recognizing opportunities. We applied bivariate genetics techniques to a sample of twins and found that a substantial part of the heritability of recognizing opportunities is mediated through genetic influences on openness to experience. Evidence of genetic effects on opportunity recognition has important implications for how companies might think about selection and training and raises important ethical issues in human resource management. ©2010 Wiley Periodicals, Inc.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.061
GPT teacher head0.265
Teacher spread0.204 · 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