MétaCan
Menu
Back to cohort
Record W1522577246

Stereotyped behaviour: resistance by people with profound learning difficulties

2006· book-chapter· en· W1522577246 on OpenAlexaboutno aff
Melanie Nind

Bibliographic record

VenueePrints Soton (University of Southampton) · 2006
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsSet (abstract data type)Resistance (ecology)PsychologyLearning disabilityControl (management)Work (physics)Public relationsSocial psychologyPolitical scienceDevelopmental psychologyEngineeringComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

The edited collection charts the course through which people with learning disabilities have become increasingly able to direct their own lives as fully active members of their communities. accounts from the UK, Australia, Canada and Iceland consider both the individual pioneers of self-advocacy and the local and national groups that have been set up to work actively towards improved services. Nind's chapter asks whether people with profound learning difficulties use behaviours that are often seen as meaningless or harmful to gain some control and to resist unwelcome demands and situations.

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)0.002
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.009
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueePrints Soton (University of Southampton)Same topicHealthcare innovation and challengesFrench-language works237,207