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Record W2042849300 · doi:10.17105/spr-13-0043.1

Utility of Number and Type of Office Discipline Referrals in Predicting Chronic Problem Behavior in Middle Schools

2014· article· en· W2042849300 on OpenAlexaff
Larissa K. Predy, Kent McIntosh, Jennifer Frank

Bibliographic record

VenueSchool Psychology Review · 2014
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologySchool disciplineSchool psychologyReferralApplied psychologyDevelopmental psychologyClinical psychologyMathematics educationSocial psychologyPedagogyMedicineFamily medicine

Abstract

fetched live from OpenAlex

Abstract. This study examined the technical adequacy of office discipline referrals (ODRs) received early in the school year for predicting total ODRs received by the end of the year. The sample included 401,852 students from 593 public middle schools (serving Grades 6 to 8) in the United States in the 2009–2010 school year. The results showed that ODRs received in September, October, and November were statistically significant predictors of total ODRs and that the inclusion of types of referrals (especially for defiance) significantly improved prediction of total ODRs. These results are discussed regarding the utility of ODRs for screening and patterns of problem behavior likely to predict chronic discipline problems in middle schools.

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 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)0.002
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 score0.068
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.315
GPT teacher head0.455
Teacher spread0.140 · 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 teacher head, not a consensus.

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

Citations16
Published2014
Admission routes1
Has abstractyes

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