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Record W1583343360 · doi:10.18061/dsq.v35i1.3762

“You’re such a good friend”: A woven autoethnographic narrative discussion of disability and friendship in Higher Education

2015· article· en· W1583343360 on OpenAlexaff
Mark Anthony Castrodale, Daniel Zingaro

Bibliographic record

VenueDisability Studies Quarterly · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsFriendshipAutoethnographyInclusion (mineral)NarrativeDisability studiesQualitative researchPsychologySociologySocial psychologyPedagogyGender studiesSocial scienceLinguistics

Abstract

fetched live from OpenAlex

In this article, the authors discuss friendship as a method of qualitative inquiry. After defining friendship and positing it as a kind of fieldwork, the methodological foundations of friendship as method are established (Tillmann-Healy, 2003). The purpose of this narrative woven autoethnographic study is to examine the role of friendship in describing disabling physical and attitudinal access barriers in a university setting. Friendship represents a critical analytic lens through which disabled/nondisabled individuals alike may examine their positions, understandings, regimes of practices, and particular knowledges. Friends —Mark and Dan — discuss their experiences of disablement and reflections on dis/ability. The authors draw from their experiences of friendship and disability in higher education and their allied identities to discuss and examine questions of access, disclosure, and inclusion.

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)0.007
metaresearch head score (Gemma)0.009
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 score0.015
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.020
Scholarly communication0.0050.009
Open science0.0010.008
Research integrity0.0030.004
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 head0.117
GPT teacher head0.405
Teacher spread0.288 · 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

Citations23
Published2015
Admission routes1
Has abstractyes

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