Conflicting Accounts of Inclusiveness in Accounting Firm Recruitment Website Photographs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In response to this special issue’s focus on new directions in auditing research, specifically its call for more analysis on the ‘real’ impact of inclusion discourses within the accounting profession, this paper critically interprets representations of gender and ethnic diversity in accounting firms’ recruitment photographs using a critical visual methodology. We analyze photographs from the recruitment websites of public accounting firms for depictions of gender and ethnic inclusiveness using a Barthesian approach. We analyze and interpret the denotative and connotative content of 1493 photographs and connotatively interpret the text and photographs in two particularly salient recruitment documents using critical semiotics. We find women (non-white individuals) make up approximately half (one quarter) of the people depicted, roughly matching trends in the population. However, women and non-white individuals are frequently depicted in subordinate roles. While they are denotatively ‘present’ in recruitment photographs, they are constructed connotatively as ‘other’ in public accounting, consistent with hegemony. Women and non-white individuals are generally constructed as outsiders, despite their numerical presence in the photographs. Accounting firms should be aware of various possible connotative interpretations of their photographs, as these interpretations may conflict with the accounts with respect to diversity and inclusion conveyed in photographs’ denotative content.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it