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Record W4407088834 · doi:10.3390/encyclopedia5010018

Likert-Type Scale

2025· article· en· W4407088834 on OpenAlexaff
Malcolm Koo, Shih-Wei Yang

Bibliographic record

VenueEncyclopedia · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicPsychometric Methodologies and Testing
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsLikert scaleScale (ratio)PsychologyStatisticsMathematicsGeographyCartography

Abstract

fetched live from OpenAlex

The Likert-type scale is a widely used psychometric instrument for measuring attitudes, opinions, or perceptions in research contexts. It presents respondents with a series of statements accompanied by symmetrical response options, typically structured on a five-point scale ranging from “Strongly Disagree” to “Strongly Agree”. Each point on the scale represents a gradation of agreement or sentiment, allowing researchers to transform subjective responses into quantifiable data for statistical analysis and interpretation.

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)0.012
metaresearch head score (Gemma)0.049
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: none
Teacher disagreement score0.086
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0860.034

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 head0.230
GPT teacher head0.476
Teacher spread0.246 · 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

Citations149
Published2025
Admission routes1
Has abstractyes

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