MétaCan
Menu
Back to cohort
Record W3201224432 · doi:10.33423/jabe.v23i1.4061

Public Opinion About the Adoption of New Technology

2021· article· en· W3201224432 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Applied Business and Economics · 2021
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPublic opinionWork (physics)Exploratory factor analysisSurvey data collectionSurvey methodologyQuestionnaireOpinion surveyPsychologyPublic relationsBusinessMarketingData scienceComputer scienceKnowledge managementOpinion leadershipPolitical scienceEngineeringSociologyMathematicsSocial scienceStatisticsLaw

Abstract

fetched live from OpenAlex

This work is a quantitative analysis of the data in a survey to understand the general factors in the mind of the people who form the public opinion about the adoption of new technology. This survey was designed as a precursor in the exploratory stage to gain understanding the tendency in the thinking of the people before designing another survey in details so that it can be applied to a subset of people who have authority to decide about an adoption of the new technology for their organizations. Due to the general nature of the desired information, a factor analysis was done to identify groups of variables that are related and relevant so that the important factors can be emphasized in the development of the second survey with more appropriate details. Data mining was applied to the data to identify the groups of participants who responded with similar data in the survey for the extraction of demographic information.

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)0.009
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.115
GPT teacher head0.329
Teacher spread0.214 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Business and EconomicsSame topicStatistical Methods and ApplicationsFrench-language works237,207