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Record W4390230426 · doi:10.5430/wje.v13n6p41

Factors Affecting Participation in Environmental Conservation of Undergraduate Students

2023· article· en· W4390230426 on OpenAlexvenueno aff
Suparat Ongon, Prayoon Wongchantra, Likhit Junkaew, Kannika Sookngam, Uraiwan Praimee, Phanat Phothibat, Wutthisak Bunnaen, Kuantean Wongchantra, Latdavahn Sommala

Bibliographic record

VenueWorld Journal of Education · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
FundersMahasarakham University
KeywordsEnvironmental educationGovernment (linguistics)PsychologyHigher educationSample (material)PedagogyEconomic growthEconomics

Abstract

fetched live from OpenAlex

The purposes of this research were to study the level of participation in the environmental conservation of undergraduate students and to study and compare the factors affecting participation in the environmental conservation of students of different genders and academic years. The sample used in the research were 231 undergraduate students of 1 - 4 years in the Environmental Education, Faculty of Environment and Resource Studies, Mahasarakham University, from voluntary sampling. The tools used in the research include participation factors in environmental conservation. The statistics used in data analysis were frequency, percentage, mean, standard deviation, and One-Way ANOVA. The results showed that: 1. The level of factors affecting participation in environmental conservation of undergraduate students, classified by aspect, it was found that undergraduate students participated in environmental conservation at a high level, equal to 3.52. When considering each aspect, it was found that all aspects were at a high level, including leadership factors, support factors (cooperation, public sector, government sector, and private sector), personal attributes factors (gender, age, year, domicile), environmental factors (economic, social, environmental cultural aspect), media factors, legal factors, educational factors, and ideological/ inspirational factors, respectively. 2. There was no difference in students who have different genders and academic years in participation in environmental conservation.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.335
Teacher spread0.311 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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