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Record W4409040122 · doi:10.1017/rsm.2024.11

Selecting a specialized education database for literature reviews and evidence synthesis projects

2025· article· en· W4409040122 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch Synthesis Methods · 2025
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceResearch methodologyDatabaseData scienceInformation retrievalMedicineEnvironmental health

Abstract

fetched live from OpenAlex

While the Institute of Education Science's ERIC is often recommended for comprehensive literature searching in the field of education, there are several other specialized education databases to discover education literature. This study investigates journal coverage overlaps between four specialized education databases: Education Source (EBSCO), Education Database (ProQuest), ERIC (Institute of Education Sciences), and Educator's Reference Complete (Gale). Out of a total of 4,695 unique journals analyzed, there are 2,831 journals uniquely covered by only one database, as well as many journals covered by only two or three databases. Findings show that evidence synthesis projects and literature reviews benefit from the careful selection of multiple specialized education databases and that ERIC is insufficient as the primary education database for comprehensive searching in the field.

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.

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)0.025
metaresearch head score (Gemma)0.141
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.971
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.141
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.220
GPT teacher head0.566
Teacher spread0.345 · 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