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Record W4411618256 · doi:10.51847/tavlxaeqpz

10.51847/tAvlXAEqPZ

2000· article· en· W4411618256 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldComputer Science
TopicInnovations in Education and Learning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityPsychologyComputer scienceSociologyHuman–computer interactionSocial psychology

Abstract

fetched live from OpenAlex

The aim of this study was to compare the creativity of students between the different groups of users in the virtual social networks.The methodology of the research was cross-sectional and comparative and collecting data is a kind of survey research.The statistical society of this study consisted of all the students who studied in Tehran Science and Research University in academic years 2016-2017.The available sampling method in this research was 200 individuals.The hypotheses of the research have been studied by using statistical methods of ANOVA.The descriptive results and the analysis of variance totally showed that the creativity of students who have the moderate activity in the virtual network (Group 2 and 3) were more than the students with extreme activity (Group 4) or with too little activity (Group 1).As a result, it can be said that the optimal usage and the amount of moderate time in the virtual social network can have a positive effect on the students' creativity; but the extreme usage of these networks causes to reduce the creativity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.930
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9350.973

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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