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Record W4411946302 · doi:10.64252/26w1nj58

Examining Vodcast's Potential to Improve Canadian Embroidery Skills in the Najran Region for Enhanced Community Sustainability

2025· article· en· W4411946302 on OpenAlexaboutno aff
Mohammed Salah-Eldin Abdel-Aziz Hassanein, Abdellah Ibrahim Mohammed Elfeky, Ayman Fawzy khttab Madkour, Marwa Yasien Helmy Elbyaly

Bibliographic record

VenueInternational Journal of Environmental Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
FundersNajran University
KeywordsSustainabilityBusinessEnvironmental planningEnvironmental resource managementGeographyEconomicsEcologyBiology

Abstract

fetched live from OpenAlex

The purpose of the current study is to determine whether Vodcast can enhance Canadian embroidery abilities in the Najran region. 60 students who were enrolled in a college of education and in their fourth academic year made up the sample. With 30 students in each group, they were randomly split into the experimental and control groups. The primary study instrument was a card for product evaluation. Results revealed that when it came to the development of Canadian embroidery abilities, students who studied through vodcasts outperformed their peers in the control group.

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 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.323
Teacher spread0.301 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

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