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Record W4416039431 · doi:10.1111/joop.70063

Negotiating identity through idiosyncratic deals: Ethnocultural minority employees and workplace stigmatization

2025· article· en· W4416039431 on OpenAlexafffund
Mouna Lachegar, Ariane Ollier‐Malaterre, Sylvie Guerrero, Mariline Comeau‐Vallée

Bibliographic record

VenueJournal of Occupational and Organizational Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIdentity (music)Flexibility (engineering)Social identity theoryForegroundingNegotiationGrounded theoryPreferenceFace (sociological concept)

Abstract

fetched live from OpenAlex

Abstract Idiosyncratic deals (i‐deals) allow employees to bargain flexibility and development opportunities proactively. The i‐deals literature has mainly examined privileged individuals, overlooking minority employees. This conceptual paper focuses on i‐deals requested by ethnocultural minority employees to cope with discrimination and one‐size‐fits‐all organizational practices. We reason that self‐verification motives grounded in a central ethnocultural identity may lead them to request accommodative i‐deals (e.g. flexibility allowing for religious rites), whereas self‐enhancement motives grounded in a central work identity may prompt them to seek growth i‐deals (e.g. responsibilities reflecting their qualification). We theorize the consequences of i‐deals requests on stigmatization through three Othering mechanisms: (1) social dominance: supervisors may grant more accommodative or growth i‐deal based on their preference for egalitarian/hierarchical relationships among social groups; (2) social identity: accommodative/growth i‐deals may heighten/attenuate out‐group status, respectively; (3) ideal worker norms: accommodative/growth i‐deals may be construed as deviation/compliance from/with ideal worker norms, respectively. Thus, i‐deals' (de)stigmatization consequences vary according to which i‐deals are obtained and in which sequence; moreover, this relationship is moderated by work group climate. Our framework contributes to the i‐deals and EDI literature by theorizing i‐deals as identity negotiation, foregrounding identity as a driver of behaviours and explaining stigmatization through distinct Othering mechanisms.

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)0.001
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 score0.282
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.093
GPT teacher head0.408
Teacher spread0.315 · 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.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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Same venueJournal of Occupational and Organizational PsychologySame topicGender Diversity and InequalityFrench-language works237,207