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Record W1554740507 · doi:10.12794/metadc271850

A Descriptive Analysis of the Use and Effect of a Self-management Project in an Undergraduate Course in Behavior Analysis

2013· dissertation· en· W1554740507 on OpenAlexaff
Michelle Lamancusa

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsDescriptive statisticsCourse (navigation)PsychologyMathematics educationEngineeringStatisticsMathematics

Abstract

fetched live from OpenAlex

Undergraduate male and female students enrolled in an introductory behavior analysis course with minimal instruction on self-management were given modified exploratory logs to use in a self-management project. Students self-monitored behavior via the log, constructed their own interventions, and reported changes in behavior and extent of success in a write up at course end. Changes in self-reported descriptions in the logs as well as the written results of a pre and post survey of emotional responses were counted. Successful self-management project interventions were reported by most students. Correspondence between planned and actual events increased. Negative reinforcement procedures characterized most students' intervention. Correspondence between events at pre and post and actual log reports was highest at post.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.339
Teacher spread0.309 · 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 designObservational
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

Citations0
Published2013
Admission routes1
Has abstractyes

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