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Record W4290839652 · doi:10.4324/9781003309192-3

Methodological Aspects

2022· book-chapter· en· W4290839652 on OpenAlexaboutno aff
Paul Vedder, Fons J. R. van de Vijver

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This chapter presents an overview of the methodological aspects of the study. It deals with a description of the sample, the sampling procedure, and the variables and instruments that were used for assessment. The chapter describes the procedures that were used for data collection and analyses. It explains the way the results are presented, focusing less on comparisons of countries or groups and more on the interrelationships among variables and clusters of variables. Adolescents were approached individually or through schools and associations. Adolescents also reported on their parents’ occupational status. In most participating countries adolescents were asked to give a letter to their parents inviting them to participate. In Australia, Canada, and the Netherlands, some parents were contacted directly by research assistants. Data were collected in all countries by the researchers themselves or by research assistants who where either postgraduate students or teachers, who were selected and trained by the main researchers in each country.

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)0.134
metaresearch head score (Gemma)0.276
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.134
Threshold uncertainty score0.707

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1340.276
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.007
Science and technology studies0.0040.003
Scholarly communication0.0070.004
Open science0.0040.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0520.018

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 head0.818
GPT teacher head0.605
Teacher spread0.213 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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