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Record W2148671719 · doi:10.1177/0145445511436006

Errorless Academic Compliance Training

2012· article· en· W2148671719 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 · 2012
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCompliance (psychology)PsychologyIntervention (counseling)AutismAutism spectrum disorderApplied behavior analysisMultiple baseline designClassroom managementHierarchyMedical educationDevelopmental psychologyPedagogySocial psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Errorless academic compliance training is a graduated, noncoercive approach to treating oppositional behavior in children. In the present study, three teaching staff in a special education classroom were trained to conduct this intervention with three male students diagnosed with autism spectrum disorders. During baseline, staff delivered a range of academic and other classroom requests and recorded student compliance. A hierarchy of compliance probabilities was then calculated, ranging from Level 1 (requests yielding high levels of compliance) to Level 4 (those typically yielding noncompliance). At treatment initiation, teaching staff delivered high densities of Level 1 requests and provided reinforcement for compliance. Subsequent request levels were faded in over time, at a slow enough rate to ensure continued high compliance. By intervention end, all three students demonstrated substantially improved compliance to classroom requests that had commonly yielded noncompliance before intervention. Covariant improvement in on-task skills was also evident.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score1.000

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)0.0010.002

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 head0.803
GPT teacher head0.490
Teacher spread0.313 · 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