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Record W1874238258 · doi:10.22230/ijepl.2015v10n2a617

Educational Contracting and the Translation of Research into Practice: The Case of Data Coach Vendors in Delaware

2015· article· en· W1874238258 on OpenAlexvenueno aff
Elizabeth Farley‐Ripple, Akisha R. Jones

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsVendorVariety (cybernetics)AccountabilityCitationBusinessPublic relationsProcess (computing)Political scienceMarketingComputer science

Abstract

fetched live from OpenAlex

Accountability puts demands on educational agencies that often exceed their capacity. As a result, a variety of educational organizations are contracted to design and implement policy. Programs and services offered by these contractors are not only instrumental in the process of mediating and implementing policy, but may also be instrumental in translating research into practice. To explore this issue, a case study is conducted using vendor proposals for Delaware’s Data Coach initiative. Data are analyzed through content and citation analyses to examine the degree and nature of research use by educational contractors. This research offers new directions for studies of research use in policy but also lessons for policymakers and practitioners that seek the services of educational contractors.

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)0.015
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.724
GPT teacher head0.629
Teacher spread0.095 · 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 designQualitative
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

Citations14
Published2015
Admission routes1
Has abstractyes

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