MétaCan
Menu
Back to cohort
Record W3186932205 · doi:10.1111/joms.12752

<i>Both</i> Diversity <i>and</i> Meritocracy: Managing the Diversity‐Meritocracy Paradox with Organizational Ambidexterity

2021· article· en· W3186932205 on OpenAlexaff
Alison M. Konrad, Orlando C. Richard, Yang Yang

Bibliographic record

VenueJournal of Management Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsWestern University
Fundersnot available
KeywordsMeritocracyDiversity (politics)Competence (human resources)SociologyPerceptionSocial psychologyPublic relationsPolitical sciencePsychologyLaw

Abstract

fetched live from OpenAlex

Abstract This conceptual paper addresses the diversity challenge organizations face as they seek to enhance opportunities for marginalized groups without damaging fairness perceptions for advantaged groups. This challenge stems from societal‐level conflicts between advantaged and marginalized groups which generate a paradoxical tension between the values of diversity and meritocracy. The diversity‐meritocracy paradox manifests in interaction as an identity validation‐threat system so that events benefitting marginalized groups threaten advantaged groups and vice versa. However, diversity and meritocracy are also interrelated, and fulfilling each of these values supports the other through their beneficial effects on organizational justice. Managing the paradox entails supporting perceptions of process integrity with diversity practices while supporting perceptions of individual competence with meritocracy practices. Balanced combinations of practices create organizational ambidexterity to fulfil diversity and meritocracy pressures simultaneously. Research is needed examining how organizations leverage the interrelatedness of diversity and meritocracy to achieve diversity, inclusion, and justice among employees.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.001
Open science0.0000.004
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 head0.070
GPT teacher head0.285
Teacher spread0.215 · 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.

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

Citations60
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Management StudiesSame topicGender Diversity and InequalityFrench-language works237,207