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Record W3008196744 · doi:10.5430/wje.v10n1p97

Gender Difference in the Scholastic Achievement Test (SAT) among School Adolescents

2020· article· en· W3008196744 on OpenAlexvenueno aff
Julie Akpotor, Elizabeth Osita Egbule

Bibliographic record

VenueWorld Journal of Education · 2020
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsnot available
Fundersnot available
KeywordsMultivariate analysis of varianceTest (biology)PsychologySignificant differenceAchievement testAcademic achievementMultivariate analysisMathematics educationGender gapDevelopmental psychologyStandardized testMathematicsStatistics

Abstract

fetched live from OpenAlex

The paper examined gender difference in the Scholastic Achievement Test (SAT) among senior secondary school adolescents using the physical science of physics in three (3) separate papers. The paper attempted to ascertain whether gender difference accounts for the score differential observed in the Scholastic Achievement Test (SAT). The study adopted a field experiment and a sample size of 410 respondents consisting of 208 males and 202 females respectively. The correlation matrix of the three (3) papers was performed and the two (2) hypotheses were tested with the quintessential Multivariate Analysis of Variance (MANOVA) at 0.05 level of significance. The results showed that the gap between males and females widened from one paper to the other with males performing better than females in physics. It was therefore recommended that some motivational strategies should be adopted to stir up female adolescents in physics and other physical sciences as a way of enhancing their career prospects in science-related disciplines.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.053
GPT teacher head0.326
Teacher spread0.273 · 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.

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

Citations10
Published2020
Admission routes1
Has abstractyes

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