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Record W2789577509 · doi:10.1037/spq0000241

Student, teacher, and classroom predictors of between-teacher variance of students’ teacher-rated behavior.

2018· article· en· W2789577509 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

VenueSchool Psychology Quarterly · 2018
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsPsychologyAkaike information criterionMultilevel modelVariance (accounting)Ethnic groupMathematics educationTeacher educationDevelopmental psychologyStatistics

Abstract

fetched live from OpenAlex

The current study examined between-teacher variance in teacher ratings of student behavioral and emotional risk to identify student, teacher and classroom characteristics that predict such differences and can be considered in future research and practice. Data were taken from seven elementary schools in one school district implementing universal screening, including 1,241 students rated by 68 teachers. Students were mostly African America (68.5%) with equal gender (female 50.1%) and grade-level distributions. Teachers, mostly White (76.5%) and female (89.7%), completed both a background survey regarding their professional experiences and demographic characteristics and the Behavior Assessment System for Children (Second Edition) Behavioral and Emotional Screening System-Teacher Form for all students in their class, rating an average of 17.69 students each. Extant student data were provided by the district. Analyses followed multilevel linear model stepwise model-building procedures. We detected a significant amount of variance in teachers' ratings of students' behavioral and emotional risk at both student and teacher/classroom levels with student predictors explaining about 39% of student-level variance and teacher/classroom predictors explaining about 20% of between-teacher differences. The final model fit the data (Akaike information criterion = 8,687.709; pseudo-R2 = 0.544) significantly better than the null model (Akaike information criterion = 9,457.160). Significant predictors included student gender, race ethnicity, academic performance and disciplinary incidents, teacher gender, student-teacher gender interaction, teacher professional development in behavior screening, and classroom academic performance. Future research and practice should interpret teacher-rated universal screening of students' behavioral and emotional risk with consideration of the between-teacher variance unrelated to student behavior detected. (PsycINFO Database Record

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.095
GPT teacher head0.399
Teacher spread0.304 · 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