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Record W2047617457 · doi:10.1177/0193841x02026004003

The Development of Science Achievement in Middle and High Schoolr

2002· article· en· W2047617457 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

VenueEvaluation Review · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsUniversity of AlbertaCanadian Institute for Advanced Research
Fundersnot available
KeywordsSocioeconomic statusMultilevel modelAcademic achievementContext (archaeology)PsychologyMathematics educationAutonomyScience educationDemographySociologyGeographyPolitical scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

Using data from the Longitudinal Study of American Youth (LSAY), hierarchical linear models (HLMs) were used to model the growth of student science achievement in three areas (biology, physical science, and environmental science) during middle and high school. Results showed significant growth in science achievement across all areas. The growth was quadratic across all areas, with rapid growth at the beginning grades of middle school but slow growth at the ending grades of high school. At the student level, socioeconomic status (SES) and age were related to the rate of growth in all areas. There were no gender differences in the rate of growth in any of the three areas. At the school level, variables associated with school context (school mean SES and school size) and variables associated with school climate (principal leadership, academic expectation, and teacher autonomy) were related to the growth in science achievement. Initial (Grade 7) status in science achievement was not associated with the rate of growth in science achievement among either students or schools in any of the three areas.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.147
GPT teacher head0.414
Teacher spread0.267 · 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