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Record W4412644031 · doi:10.1111/1911-3846.13061

Cashiers' contribution to organizations: A feminist perspective of accounting and countering

2025· article· en· W4412644031 on OpenAlexvenueno aff
Nathalie Clavijo, Claire Dambrin

Bibliographic record

VenueContemporary Accounting Research · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
FundersAcademy of Finland
KeywordsPerspective (graphical)AccountingBusinessSociologyArt

Abstract

fetched live from OpenAlex

Abstract This paper examines how a low‐skilled, gendered occupational group collectively counters representations of its contribution to organizational performance. We situate this process within the literature on counter accounts—alternative representations designed to rectify perceived harms or injustices. Our study focuses on cashiers, referred to as “checkout hostesses” in their organization's gendered terminology, in the highly masculine building supplies sector. Drawing on a feminist theorization of counter accounts and a 1‐year ethnography at two levels (in a store and in a cashiers' working group), we show that cashiers produce three counter accounts: (1) a vocational qualification that highlights their accounting and selling skills, (2) a reframing of their customer credit activities as a contribution to sales, and (3) a quantification of their selling activity in a dashboard tracking sales at the checkout. These counter accounts challenge patriarchal social structures that frame their job as a low‐status “woman's job,” objectify them, and overshadow their contribution to organizational performance. We advance the concept of counter accounts from the inside, showing that they do not merely denounce oppression but also repurpose stereotypical gender and class norms as resources for collective empowerment. We also emphasize how internal organizational support fosters occupational groups' awareness of their agency. Finally, we argue that the potential and limitations of counter accounts must be assessed from the perspective of the vulnerable group itself, broadening their understanding as emancipatory tools produced for the “other” by the “other.”

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0140.035
Scholarly communication0.0070.006
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.032
GPT teacher head0.330
Teacher spread0.298 · 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 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

Citations3
Published2025
Admission routes1
Has abstractyes

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