MétaCan
Menu
Back to cohort
Record W2893908497 · doi:10.1097/phh.0000000000000834

Expanded In-School Instructional Time and the Advancement of Health Equity: A Community Guide Systematic Review

2018· review· en· W2893908497 on OpenAlexaff
Yinan Peng, Ramona Finnie, Robert A. Hahn, Benedict I. Truman, Robert L. Johnson, Jonathan E. Fielding, Carles Muntaner, Mindy T. Fullilove, Xinzhi Zhang

Bibliographic record

VenueJournal of Public Health Management and Practice · 2018
Typereview
Languageen
FieldSocial Sciences
TopicYouth Substance Use and School Attendance
Canadian institutionsUniversity of Toronto
FundersNational Institutes of Health
KeywordsEthnic groupEquity (law)Health equityAcademic achievementMedical educationPsychologyEducational equityTest (biology)MedicineFamily medicineGerontologyMathematics educationPolitical scienceNursingPedagogyPublic health

Abstract

fetched live from OpenAlex

Expanded in-school instructional time (EISIT) may reduce racial/ethnic educational achievement gaps, leading to improved employment, and decreased social and health risks. When targeted to low-income and racial/ethnic minority populations, EISIT may thus promote health equity. Community Guide systematic review methods were used to search for qualified studies (through February 2015, 11 included studies) and summarize evidence of the effectiveness of EISIT on educational outcomes. Compared with schools with no time change, schools with expanded days improved students' test scores by a median of 0.05 standard deviation units (range, 0.0-0.25). Two studies found that schools with expanded day and year improved students' standardized test scores (0.04 and 0.15 standard deviation units). Remaining studies were inconclusive. Given the small effect sizes and a lack of information about the use of added time, there is insufficient evidence to determine the effectiveness of EISIT on academic achievement and thus health equity.

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)0.102
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.790
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.236
GPT teacher head0.494
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Public Health Management and PracticeSame topicYouth Substance Use and School AttendanceFrench-language works237,207