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Record W4200210010 · doi:10.1002/2211-5463.13345

Science students' perspectives on how to decrease the stigma of failure

2021· article· en· W4200210010 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFEBS Open Bio · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStigma (botany)CurriculumContext (archaeology)PsychologyPerceptionTheme (computing)PedagogyEngineering ethicsMedical educationMedicineEngineeringBiologyComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

Failure is hard-wired into the scientific method and yet teaching students to productively engage with failure is not foundational in most biology curricula. To train successful scientists, it is imperative that we teach undergraduate science students to be less fearful of failure and to instead positively accept it as a productive part of the scientific process. In this article, we focus on student perceptions of the stigma of failure and their associated concerns to explore how failure could be better supported within and beyond a university context. Through a survey of first-year biology students, we found that societal and familial pressures to succeed were the greatest contributing factors to students' fear of failure. In student suggestions on how to reduce the stigma of failure within and beyond the university context, the most common theme identified across both contexts was for increased discussion and open communication about experiences of failure. Importantly, student comments in this study bring attention to the role of factors beyond the classroom in shaping student experiences of failure within their biology courses.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.218
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.338
Teacher spread0.301 · 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