MétaCan
Menu
Back to cohort
Record W776610587

National Study of Living-Learning Programs: 2007 Report of Findings

2008· article· en· W776610587 on OpenAlexfundno aff
Karen Kurotsuchi Inkelas

Bibliographic record

VenueDigital Repository at the University of Maryland (University of Maryland College Park) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
FundersEuropean Social FundIllinois State UniversityMichigan State UniversityUniversity of South CarolinaState University of New YorkCollege of Engineering, Michigan State UniversitySyracuse UniversityUniversity of MissouriGeorge Washington UniversityNorthern Illinois UniversityColorado State UniversityUniversity of California, IrvineUniversity of Wisconsin-MadisonOhio State UniversityYork UniversitySan José State UniversityUniversity of MiamiBowling Green State UniversityEdna Bailey Sussman FoundationOregon State UniversityGeorge Mason University
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

This comprehensive report of findings presents the results from a survey of over 22,000 undergraduates representing over 40 American postsecondary institutions. The study examines the contributions of participation in a living-learning program on undergraduate student outcomes. Results are presented by institutional type, living-learning program type, longitudinal findings, and outcomes for women who are science, technology, engineering, and mathematics (STEM) majors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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

Citations69
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository at the University of Maryland (University of Maryland College Park)Same topicEducation Systems and PolicyFrench-language works237,207