Scripting professional identities: how individuals make sense of contradictory institutional logics
Bibliographic record
Abstract
This article examines how individual accountants subjectively interpret competing logics of professionalism as they transform from practicing accountants to managerial roles and as their organizations transform from traditional professional partnerships to more corporate organizational forms. Based on a longitudinal ethnography of professionals in a Big Four accounting firm we analyse the process by which individual professionals make sense of their new roles and integrate the conflicting demands of professional and managerial logics. We find that individuals are active authors of their own identity scripts . We further observe considerable interpretive variation in how identity scripts are reproduced and enacted. We contribute to the emerging understanding of institutions as ‘inhabited’ by individuals and extend this literature by demonstrating that the institutional work of reinterpreting competing logics is based less of inter-subjective interactions, as prior literature has assumed, and is, instead, based on individual cognition and interpretive subjectivity. We also contribute to research in professional service firms by offering a conceptual model of the individual micro-processes required for successful archetypal change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".