MétaCan
Menu
Back to cohort
Record W7052067622

Purposes, Policies, Performance Higher Education and the Fulfillment of a State’s Public Agenda

2003· article· en· W7052067622 on OpenAlexfundno aff

Bibliographic record

VenueVTechWorks (Virginia Tech) · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersYork University
KeywordsHigher educationGovernment (linguistics)State (computer science)Public policyState governmentEducation policyState policyHigher education policy
DOInot available

Abstract

fetched live from OpenAlex

In the United States, the primary responsibility for education lies with individual states. To be sure, the federal government plays an enabling role, particularly in higher education; its programs of financial aid and assistance create opportunity for millions of Americans, helping ensure that those who seek a higher education can do so regardless of their financial circumstance. But it is states that create the particular environment for education, not just in the primary and secondary levels but also in the domain of higher education. This report examines the policy environments in two states in the United States: New Jersey and New Mexico. Through an extensive series of interviews with state policy officials as well as data collection and analysis, this report analyses the relationship between the higher education policy environment and the grades these two states attained on the report card’s measures.

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)0.017
metaresearch head score (Gemma)0.023
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0150.014
Scholarly communication0.0170.007
Open science0.0010.005
Research integrity0.0030.004
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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueVTechWorks (Virginia Tech)Same topicMagnetic confinement fusion researchFrench-language works237,207