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Record W2804532730 · doi:10.15173/ijsap.v2i1.3372

Resistances and resiliencies in student-faculty pedagogical partnership

2018· article· en· W2804532730 on OpenAlexvenueno aff
Anita Ntem, Alison Cook‐Sather

Bibliographic record

VenueInternational Journal for Students as Partners · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
FundersHaverford College
KeywordsGeneral partnershipResistance (ecology)Context (archaeology)PsychologyPedagogyMedical educationPolitical scienceMedicine

Abstract

fetched live from OpenAlex

In this article, we explore forms of psychological resistance that 10 female students perceived in their faculty partners and in themselves in the context of a pedagogical partnership program in the mid-Atlantic region of the United States. Positioning these students as “holders and creators of knowledge” (Delgado-Bernal, 2002, p. 106), our analysis draws on literature in academic development and psychology and on student responses to research questions to discuss how these student partners built resiliencies through the approaches they took to engaging the resistances they perceived. We first present the resistances these student partners perceived in their faculty partners and what factors they think might have contributed to such resistances. Next, we describe the approaches the student partners took to working through the resistances they perceived and the resistances they experienced in themselves. Finally, we analyze the ways that student partners developed resiliencies through productively engaging these forms of resistance.

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)0.013
metaresearch head score (Gemma)0.029
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 score0.014
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0120.026
Scholarly communication0.0140.008
Open science0.0020.030
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.285
GPT teacher head0.657
Teacher spread0.373 · 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

Citations35
Published2018
Admission routes1
Has abstractyes

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