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Record W2903034924 · doi:10.1002/jeab.488

Baseline reinforcement rate and resurgence of destructive behavior

2018· article· en· W2903034924 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

VenueJournal of the Experimental Analysis of Behavior · 2018
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsBrock University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human Development
KeywordsReinforcementBaseline (sea)Extinction (optical mineralogy)Context (archaeology)PsychologyReinforcement learningArtificial intelligenceSocial psychologyComputer scienceBiology

Abstract

fetched live from OpenAlex

Concepts from behavioral momentum theory, along with some empirical findings, suggest that the rate of baseline reinforcement may contribute to the relapse of severe destructive behavior. With seven children who engaged in destructive behavior, we tested this hypothesis in the context of functional communication training by comparing the effects of different baseline reinforcement rates on resurgence during a treatment challenge (i.e., extinction). We observed convincing resurgence of destructive behavior in four of seven participants, and we observed more resurgence in the condition associated with high-rate baseline reinforcement (i.e., variable-interval 2 s in Experiment 1 or fixed-ratio 1 in Experiment 2) compared to a low-rate baseline reinforcement condition. We discuss the implications of these results relative to schedules of reinforcement in the treatment of destructive behavior and strategies to mitigate resurgence in clinical settings.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.121
GPT teacher head0.385
Teacher spread0.264 · 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