"What am I doing here?" Imposter syndrome and institutional structures propagating feelings of inadequacy among graduate students
Bibliographic record
Abstract
We have all felt incredibly inadequate at some point in our lives. The pervasive thought that “everybody is more brilliant than me” is more common than we think. However, how often do we think of it as being propagated by institutional factors? My study examines how imposter syndrome, structural constraints, and their meanings interplay in academia. I spoke to 20 graduate students from different faculties, backgrounds, and genders at the Memorial University of Newfoundland (MUN) via semi-structured interviews. I found that participants frequently used impression management techniques, consistently showcasing skills, achievements, or levels of knowledge through their narrations. Participants approached imposter syndrome mainly as an internal personal issue, constantly comparing themselves to other people’s situations. In doing so, they used a single definition of success or failure in academia. However, the data showed that structural factors, such as racism, patriarchy, colonialism, a working yourself-to-the-bone culture, lack of support from gatekeepers, and COVID-19, all had an immense impact on feelings of inadequacy and self-doubt among graduate students.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| 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".