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Record W2012807080 · doi:10.1080/13611267.2015.1011038

Reducing Intellectual Poverty of Outsiders within Academic Spaces through Informal Peer Mentorship

2015· article· en· W2012807080 on OpenAlex
Joyanne De Four-Babb, Jerine Pegg, Makini Beck

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

VenueMentoring & Tutoring Partnership in Learning · 2015
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMentorshipInvisibilityPovertyNarrativeSociologyPeer mentoringPublic relationsPolitical sciencePedagogy

Abstract

fetched live from OpenAlex

Academia is changing and a growing number of academics are finding themselves in non-tenure-track positions, experiencing increasing numbers of career transitions, or following alternative career trajectories. Academics in these positions often find themselves positioned as outsiders within their institutions and/or the broader academic community. In this article, the authors draw on narratives from eight members of an international peer mentoring group to examine the nature of being an outsider within academia, and the role that informal peer mentoring can play in reducing intellectual poverty for academics in outsider spaces. The findings illuminate the nature of intellectual poverty they experienced—including isolation and invisibility—lack of access to institutional knowledge, and lack of resources for professional development. The participants’ narratives also highlight the ways in which peer mentoring enhanced their professional development, allowed participants to access support beyond institutional and geographic boundaries, and provided social support and motivation to move forward in scholarly pursuits.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.123
GPT teacher head0.373
Teacher spread0.249 · 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