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Record W4288297323 · doi:10.5281/zenodo.3354089

Panelist Sessions and Ph.D. Studies: UTAUT approach

2019· article· en· W4288297323 on OpenAlex
Kezia H. Mkwizu, Sumaya Kagoya M

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

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typearticle
Languageen
FieldPsychology
TopicTechnostress in Professional Settings
Canadian institutionsIndustry, Tourism and Investment
Fundersnot available
KeywordsComputer sciencePsychology

Abstract

fetched live from OpenAlex

The purpose of this paper is to examine panelist sessions and Doctor of Philosophy (Ph.D.) studies with the specific objective of analyzing Information Communication Technology (ICT) usage in panelist sessions and success in completion of Ph.D. studies. The study framework is guided by the Unified Theory of Acceptance and Use of Technology (UTAUT). Study area is Tanzania. Quantitative method is utilized and semi-structured questionnaires were distributed to respondents at a public university using convenience sampling. The techniques used for analyzing collected data were descriptive statistics and Partial Least Square Structural Equation Modelling (PLS-SEM) assisted with SmartPLS 3. The results revealed a significant relationship between ICT usage in panelist sessions and success in completion of Ph.D. studies (<em>p = 0.000</em>).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.633
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.011

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 head0.070
GPT teacher head0.340
Teacher spread0.270 · 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