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Record W4320486674 · doi:10.1037/apl0001072

Do you see me? An inductive examination of differences between women of color’s experiences of and responses to invisibility at work.

2023· article· en· W4320486674 on OpenAlexafffundabout
Barnini Bhattacharyya, Jennifer L. Berdahl

Bibliographic record

VenueJournal of Applied Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of British ColumbiaWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInvisibilityIntersectionalitySocial psychologyPsychologyPsycINFOPower (physics)Gender studiesWomen of colorSociologyRace (biology)Political science

Abstract

fetched live from OpenAlex

Intersectional invisibility is a salient experience for women of color in the workplace and stems from their nonprototypicality in gender and race. We expand research and theory on intersectional invisibility to propose that women of color vary in their degrees of nonprototypicality, and thus in their social power and their experiences of and responses to invisibility at work. We present an inductive interview study of a diverse sample of 65 women of color in the United States and Canada, who work in traditionally white and male professions. We examined how differences in race, immigration status, age, and organizational rank informed the types of invisibility they experienced and their responses to invisibility. Four forms of invisibility (erasure, homogenization, exoticization, and whitening) and three response pathways (withdrawal, approach, and pragmatism) emerged from our findings that differed according to women of color's social power. Women with less social power experienced the most invisibility and were more likely to engage in withdrawal tactics that intensified their invisibility and marginalization at work. Women with more social power experienced less invisibility and were more likely to engage in approach tactics that risked backlash. Women who understood their invisibility to be rooted in structural causes responded more pragmatically to invisibility, occasionally engaging in radical honesty to connect with others who treated them as invisible and to change their behavior. We discuss the implications of our research for intersectionality theory, directions for future research, and organizational practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.189
GPT teacher head0.396
Teacher spread0.207 · 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 designQualitative
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

Citations36
Published2023
Admission routes3
Has abstractyes

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