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Record W2902931191 · doi:10.22230/ijepl.2018v13n11a765

An Exploratory Analysis of the Prevalence of Quantitative Research Concepts in Journal Articles

2018· article· en· W2902931191 on OpenAlexvenueno aff
Craig Hochbein, Katherine S. Smeaton

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsExploratory analysisExploratory researchQuantitative analysis (chemistry)Educational researchLibrary sciencePsychologyMedical educationSociologySocial scienceMedicineData scienceComputer science

Abstract

fetched live from OpenAlex

The purpose of this study is to explore the prevalence of quantitative researchmethodologies in published journal articles to better understand the knowledge andskills necessary for school leaders to meet the expectations of applying research findingsto practice. It examines research articles published between 2008 and 2013 inthe American Educational Research Journal, the Educational Administration Quarterly,and the NASSP Bulletin. Empirical articles comprise 91 percent of the 449 identifiedresearch articles, with 58 percent reporting the use of quantitative methodolog.

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)0.006
metaresearch head score (Gemma)0.005
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 score0.073
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
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 head0.607
GPT teacher head0.609
Teacher spread0.002 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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