MétaCan
Menu
Back to cohort
Record W2149419783 · doi:10.1177/0145445506295050

Errorless Compliance Training

2007· article· en· W2149419783 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehavior Modification · 2007
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsLearning PartnershipUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychologyCompliance (psychology)Intervention (counseling)Rendering (computer graphics)Developmental psychologySocial psychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

Errorless compliance training is a noncoercive, success-focused approach to treatment of problem behavior in children. The intervention involves graduated exposure of a child to increasingly more challenging requests at a slow enough rate to ensure that noncompliance rarely occurs, providing parents with many opportunities to reinforce cooperative responses and rendering punishment unnecessary. The authors evaluated this approach with three boys with characteristics of Asperger syndrome. Mothers first delivered a range of requests to their children and recorded child responses. For each child, the authors calculated compliance probability for all requests and categorized them into four probability levels, from those yielding high compliance (Level 1) to those that commonly led to opposition (Level 4). Treatment began with delivery of Level 1 requests. Requests from Levels 2 through 4 were faded in sequentially over several weeks. All three children demonstrated substantial generalized improvement in compliance.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.378
GPT teacher head0.432
Teacher spread0.054 · 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