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Record W2009515497 · doi:10.1177/0145445503258990

Agreement of Function Across Methods Used in School-Based Functional Assessment With Preadolescent and Adolescent Students

2004· article· en· W2009515497 on OpenAlexaff
Meg M. Kwak, Ruth A. Ervin, Mary Z. Anderson, John Austin

Bibliographic record

VenueBehavior Modification · 2004
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyFunction (biology)Rating scaleMainstreamApplied psychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

As we begin to apply functional assessment procedures in mainstream educational settings, there is a need to explore options for identifying behavior function that are not only effective but efficient and practical for school personnel to employ. Attempts to simplify the functional assessment process are evidenced by the development of informant assessment measures (e.g., interviews, rating scales). In this study, the agreement (i.e., on relative rankings and primary function) across sources of information regarding behavior function was examined for 19 students in a middle school setting. These measures included teacher ratings, student ratings, student interviews, observer ratings, and conditional probabilities. In addition, for 1 student, whether information obtained through these sources was consistent with that obtained through a brief analog analysis of function was examined. Results indicated low agreement regarding rank order of behavior function and on primary function across all sources of information.

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)0.021
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.060
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.298
GPT teacher head0.476
Teacher spread0.178 · 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.

Study designObservational
DomainMethods
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

Citations17
Published2004
Admission routes1
Has abstractyes

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