Borrowed Time: ‘Identity as Liability’ – A Critical Discourse Analysis of Imposter Syndrome in Social Workers with Disabilities
Bibliographic record
Abstract
This major research paper investigates the discourse of imposter syndrome, and how it is understood and affects disabled social workers/social service workers/social work learners. My research question asks: what are the discourses on imposter syndrome in social work and how do they intersect with disability? Using the method of critical discourse analysis (CDA) – informed interviews, I conducted 5 interviews with participants to ask how they understand and experience imposter syndrome with respect to disability. I found that all participants felt the immense impacts of imposter syndrome in the form of upward comparisons, self-doubting, heightened distress, procrastination, and perfectionism. Participants were able to recognize the compounded effects of imposter syndrome on their lives as a result of holding differing identity markers such as: race, sexual orientation, gender identity, type of disability, etc. Social work needs to make room for talk about imposter-hood and challenge the notions of the “ideal social worker”.
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 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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.011 | 0.034 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".