Bibliographic record
Abstract
Coined by researchers Dr. Pauline Clance and Dr. Suzanne Imes in 1978, the impostor phenomenon (IP) describes the experience of doubting one’s skills, intellect, and talents despite one’s many achievements. The phenomenon was originally studied amongst high-achieving White women from various professional fields and over time has been conceptualised as an internal psychological experience. As a result, recommendations to address IP have mostly focused on intervening at an individual or micro level. More recently, research on IP has expanded to include racially marginalised populations, including college students who identify as Black/African American. While more research needs to be done around how Black/African American students experience IP, recent studies have indicated a relationship between IP and experiences of racial discrimination for Black/African American students. Taking into consideration the collective history of racism, discrimination, and exclusion that Black students have faced within higher education institutions in the U.S. and abroad, and that they continue to currently face, the experience of IP may be more than just an internal psychological experience. The purpose of this paper is to provide a reframing in the way that IP is discussed as it relates to Black/African American college students. This paper argues that for Black students, the experience of IP is more than just an internal reaction but is instead a byproduct of structural racism and white supremacist norms that continue to be present within higher education today. Recommendations for how higher education institutions can begin to address IP at both micro and macro levels will also be discussed.
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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.031 | 0.023 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.007 | 0.022 |
| 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".