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Record W2616930902 · doi:10.1177/0003122417703087

The Effects of Gendered Occupational Roles on Men’s and Women’s Workplace Authority: Evidence from Microfinance

2017· article· en· W2616930902 on OpenAlexaff
Laura Doering, Sarah Thébaud

Bibliographic record

VenueAmerican Sociological Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsMcGill University
FundersEwing Marion Kauffman Foundation
KeywordsMicrofinanceCompliance (psychology)Variety (cybernetics)Demographic economicsBusinessPolitical scienceGender studiesPsychologySocial psychologySociologyEconomics

Abstract

fetched live from OpenAlex

The gendering of occupational roles affects a variety of outcomes for workers and organizations. We examine how the gender of an initial role occupant influences the authority enjoyed by individuals who subsequently fill that role. We use data from a microfinance bank in Central America to examine how working initially with a male or female loan manager shapes borrowers’ compliance with future managers’ directives. First, we show that borrowers originally paired with female managers continue to be less compliant with subsequent managers, regardless of subsequent managers’ gender. Next, we demonstrate how compliance is shaped by the gender-typing of the role and the gender of the individual who fills that role. We find that men enjoy significantly greater compliance in male-typed roles, but male and female managers experience similar levels of compliance in female-typed roles. Further analyses reveal that these gendered patterns become especially pronounced after managers demonstrate their authority by disciplining borrowers. Overall, we show how quickly gendered expectations become inscribed into occupational roles, and we identify their lasting organizational consequences. More broadly, we suggest authority mechanisms that may contribute to the “stalled” gender revolution in the workplace.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.124
GPT teacher head0.383
Teacher spread0.259 · 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

Citations65
Published2017
Admission routes1
Has abstractyes

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