MétaCan
Menu
Back to cohort
Record W3008850776 · doi:10.5267/j.msl.2020.2.023

Modeling the social, economic and environmental effects of Pondok Tahfiz

2020· article· en· W3008850776 on OpenAlexvenueno aff
Hasannuddiin Hassan, Mohd Ikhwan Aziz, Rohana Rohana, Salwani Salwani, Arbaiah Arbaiah, Hakimin Hakimin, Asyraf Afthanorhan

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySocial psychologyEnvironmental economicsEconomics

Abstract

fetched live from OpenAlex

This paper aims to model the social, economic and environmental (SEE) impacts of Pondok Tahfiz in Kelantan.The basic principle of a sustainable development paradigm lies in three aspects; namely social, economic, and environmental.These aspects guide the management of human use of resources so that any development project may yield the greatest sustainable benefits or positive impacts to present generations while maintaining the ability to meet the needs of future generations.Pondok tahfiz is the orthodox Islamic school institution that focus on Islamic education learning.Presently, the institution is highly demanded among Muslim Malaysian as they believe the institution provides some benefits in future.The three aspects of SEE are commonly used as dimensions for measuring impacts of sustainable development of Pondok tahfiz.Through this, SEE is able to acquire indirect and direct impacts of education institute towards social, economy and environment.The findings indicate that all the dependent variables provide a significant impact towards sustainable development of pondok tahfiz.However, the economic development provides less impact for the sustainable development.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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 designSimulation or modeling
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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueManagement Science LettersSame topicTransboundary Water Resource ManagementFrench-language works237,207