What happens when you can’t be <i>who you are</i> : Professional identity at the institutional periphery
Bibliographic record
Abstract
This article examines the impact of large scale, ‘macro’ role transitions on professional identity. Drawing on in-depth interviews with two different groups of immigrant professionals, it theorizes how organizational outsiders with established professional identities respond to the institutional requirements and specifically to professional pre-entry scripts in their new host country. The study demonstrates how identity work evolves among each group as they navigate the permeable and impermeable pre-entry scripts in their respective professions. It identifies both barriers and facilitators to engagement with, and fulfillment of, local pre-entry scripts. These findings demonstrate how different professional domains and power structures create different opportunities for re-entry and as a result give rise to different forms of identity work – involving, for example, identity customization, identity shadowing, struggle and enrichment. Implications for policy makers in the field will be discussed, focusing on how different groups of professionals respond to unique forms of identity threat emerging from their respective professional institutions and structural barriers.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".