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Record W4410205048 · doi:10.5840/symposium20252916

Towards a World That Stutters

2025· article· en· W4410205048 on OpenAlexvenueno aff
Joshua St. Pierre, Danika Jorgensen Skakum

Bibliographic record

VenueSymposium · 2025
Typearticle
Languageen
FieldPsychology
TopicStuttering Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceBiologyComputational biology

Abstract

fetched live from OpenAlex

This article explores three conceptual modes of belonging within the stuttering community—curative, inclusive, and transformative—each reflecting distinct relationships to disability, social relations, and political action. Curative belonging operates within an ableist framework, positioning fluency as a prerequisite for belonging. In the mode of inclusion, people who stutter seek belonging within existing societal relations and must contort themselves appropriately. Transformative belonging, by contrast, reimagines dys-fluency as a generative difference, challenging the dominance of fluency and advocating for a world that embraces stuttering on its own terms. By mapping these modes, this article highlights the tensions within the stuttering community and argues for a political shift that moves beyond tolerance and integration towards an affirmative vision of dysfluency as a site of resistance and belonging.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0170.033
Scholarly communication0.0130.010
Open science0.0010.014
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.029
GPT teacher head0.353
Teacher spread0.324 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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