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Record W4389037270 · doi:10.55016/ojs/ajer.v69i3.76167

“I wasn’t that good at it but I pretended to be”: Students’ Experiences of the Impostor Phenomenon in Academic Settings

2023· article· en· W4389037270 on OpenAlexaffvenue
A. Dana Ménard, Michelle Bondy, Madison Jones, Lauren Desjardins, Lana Milidrag, Alanna Foulon, Laura Chittle

Bibliographic record

VenueAlberta Journal of Educational Research · 2023
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsUniversity of OttawaUniversity of Windsor
Fundersnot available
KeywordsFeelingPsychologyHumanitiesConvictionPhenomenonSocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

The impostor phenomenon (IP) is an internalized feeling of fraudulence characterized by beliefs that one’s personal successes are due to external factors (e.g., luck) rather than internal attributes. Individuals who suffer from impostor feelings may feel that they are not really intelligent or capable but have instead fooled others. Written descriptions of IP experiences were provided by 879 graduate and undergraduate students and submitted to content analysis. Nine major themes were identified across three categories: causes (i.e., novel experiences, challenges, everyday academic interactions, and high expectations), feelings and impact (i.e., negative psychophysiological symptoms and negative thoughts and emotions), and management (i.e., negative, neutral, and positive). Implications for addressing these feelings in post-secondary settings are considered. Keywords: higher education; individual differences; stress/coping; content analysis; qualitative research Le phénomène de l'imposteur (PI) est un sentiment de fraude intériorisé, caractérisé par la conviction que les succès personnels sont dus à des facteurs externes (par exemple, la chance) plutôt qu'à des attributs internes. Les personnes qui souffrent du sentiment d'imposture peuvent avoir l'impression qu'elles ne sont pas vraiment intelligentes ou capables, mais qu'elles ont plutôt trompé les autres. Des descriptions écrites d'expériences de PI ont été fournies par 879 étudiants de premier et deuxième cycles et ont été soumises à une analyse de contenu. Neuf thèmes principaux ont été identifiés dans trois catégories : les causes (expériences nouvelles, défis, interactions académiques quotidiennes et attentes élevées), les sentiments et l'impact (symptômes psychophysiologiques négatifs, pensées et émotions négatives) et la gestion (négative, neutre et positive). Les implications de la prise en compte de ces sentiments dans le cadre de l'enseignement post-secondaire sont examinées. Mots clés : enseignement supérieur ; différences individuelles ; stress/capacités d’adaptation ; analyse de contenu ; recherche qualitative

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.012
Scholarly communication0.0070.005
Open science0.0010.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.138
GPT teacher head0.473
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes2
Has abstractyes

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