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Record W2006039039 · doi:10.1332/174426406775249705

Information retrieval and the role of the information specialist in producing high-quality systematic reviews in the social, behavioural and education sciences

2006· article· en· W2006039039 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

VenueEvidence & Policy · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsConcordia University
Fundersnot available
KeywordsSystematic reviewSet (abstract data type)Quality (philosophy)Process (computing)Knowledge managementBest practiceInclusion (mineral)Computer sciencePublic relationsPolitical sciencePsychologyMEDLINE

Abstract

fetched live from OpenAlex

English The International Campbell Collaboration (C2) prepares, maintains and disseminates high-quality systematic reviews in the social, behavioural and educational sciences. As part of its effort to ensure that systematic reviews are based on a set of systematic, transparent and replicable procedures, C2 has produced a set of policy briefs. One of these, the C2 Information retrieval policy brief , proposes policies for searching the literature for C2 reviews, addresses key issues and challenges faced by C2 reviewers, and recommends working with an information specialist (IS). This article illustrates how the information retrieval issues raised in the brief have been addressed by one C2 review team, through the inclusion of an IS as an integral member of its review team. This unique approach recognises that information retrieval is a continuous and important process, requiring the ongoing expertise of a professional. Cost implications for the provision of ongoing support by an IS are briefly addressed, along with various alternative approaches.

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)0.154
metaresearch head score (Gemma)0.079
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1540.079
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.479
GPT teacher head0.518
Teacher spread0.039 · 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