MétaCan
Menu
Back to cohort
Record W4236587896 · doi:10.22215/etd/2018-13329

Inspiring or Perpetuating Stereotypes?: The Complicated Case of Disability as Inspiration

2018· dissertation· en· W4236587896 on OpenAlexaff
Leah Cameron

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsCarleton University
Fundersnot available
KeywordsNarrativeDisabled peopleFocus groupSocial mediaQualitative researchPerceptionDisability studiesGovernment (linguistics)PsychologyGender studiesMedia studiesSociologyPublic relationsPolitical scienceApplied psychologySocial scienceArtLawLiterature

Abstract

fetched live from OpenAlex

This research looks at how inspirational narratives that feature disability, also known as "inspiration porn", are interpreted by disabled and non-disabled audiences.The project usesWe're The Superhumans, a British infomercial for the 2016 Summer Paralympic Games in Rio de Janeiro, as its case study.This research is informed by social science research on disability, critical media studies literature, as well as government documents and official reports.Qualitative data were gathered through focus groups with disabled and non-disabled participants, as well as through comments posted on the infomercial's YouTube video and on Twitter, and through media coverage.The results of the study show that reactions to inspirational narratives are not uniform among disabled and non-disabled audiences and that negative perceptions of disability persist.This study provides valuable insight regarding the nuances and complexities surrounding inspiration porn and social attitudes towards disability.Summary of findings ....

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)0.008
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: Other
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.048
Scholarly communication0.0110.013
Open science0.0010.014
Research integrity0.0030.004
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 head0.065
GPT teacher head0.418
Teacher spread0.352 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicDisability Rights and RepresentationFrench-language works237,207