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Record W3110822676 · doi:10.15353/cjds.v8i3.508

Shifting neurotypical prevalence in knowledge production about the mentally diverse: A qualitative study exploring factors potentially influencing a greater presence of lived experience-led research

2019· article· en· W3110822676 on OpenAlexvenueno aff
Damian Mellifont

Bibliographic record

VenueCanadian Journal of Disability Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPsycINFOInclusion (mineral)RedressQualitative researchMental healthPsychologyScopusThematic analysisNeurotypicalPublic relationsMEDLINESocial psychologyPolitical scienceSociologyPsychiatrySocial scienceAutism

Abstract

fetched live from OpenAlex

Research which is led by mentally diverse persons offers a variety of benefits. Crucially, this research holds potential to target wide-ranging social inclusion issues. Recognizing that these studies cannot lay claim to be commonplace, the aim of this investigation is to inform and improve policy supportive of lived experience-led studies by critically investigating evidence-based factors influencing a greater presence of this genuinely inclusive style of research. Following purposive sampling, thematic analysis was applied to twelve articles meeting with inclusion criteria and retrieved from Scopus, Medline, PsycINFO and ProQuest databases. This investigation reveals three key findings. First, this exploratory study identifies factors supporting and resisting lived experience-led research across micro, meso and macro levels. Second, investment in future research is needed to identify evidence-based measures with capacity to redress factors constraining opportunities for mentally diverse persons to develop research careers and to potentially lead the way in reforming mental health and other services. Finally, any assertions of neurodiverse researchers as necessarily being lacking in professional qualifications or reliant upon the assistance of neurotypical colleagues should be critically questioned.

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)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.399
GPT teacher head0.497
Teacher spread0.098 · 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.

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

Citations8
Published2019
Admission routes1
Has abstractyes

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