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Record W2991192735 · doi:10.15353/cjds.v8i5.568

Our Madness is Invisible: Notes on Being Privileged (Non)Disabled Researchers

2019· article· en· W2991192735 on OpenAlexaffvenue
Matthew S. Johnston, Matthew D. Sanscartier

Bibliographic record

VenueCanadian Journal of Disability Studies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCarleton University
Fundersnot available
KeywordsPrivilege (computing)Identity (music)NegotiationEmancipationAutoethnographySociologyDisability studiesConstitutionAbleismMental healthGender studiesPsychologyPolitical scienceLawAestheticsSocial sciencePoliticsPsychotherapist

Abstract

fetched live from OpenAlex

This autoethnographic piece traces how two researchers continually negotiate their privileges, successes, insecurities, challenges, and (non)disabled identities in the neoliberal academy. We interrogate the co-constitution of identity of (1) a mentally disabled researcher and graduate student who researches madness in the midst of dealing with his own struggles maintaining a professional identity and repairing a fractured self; (2) a non-disabled doctoral student who has found academic success, but has had his life stalled multiple times by significant mental health challenges. We propose the concept of the privileged (non)disabled self to capture how researchers become entangled in permanent or temporal disabilities while simultaneously negotiating their accomplishments. We encourage researchers not to sideline their reflections on privilege and disability as irrelevant, but continually examine their identities in order to reveal potential avenues for emancipation.

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 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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.465
GPT teacher head0.510
Teacher spread0.045 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2019
Admission routes2
Has abstractyes

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