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Record W4386245935 · doi:10.18280/ijsdp.180809

Assessment of Community Awareness and Knowledge of Environmental Law and Legislation in the Basrah Governorate (Iraq)

2023· article· en· W4386245935 on OpenAlexvenueno aff
Mohammad S. Moyel, Nadia Al‐Mudaffar Fawzi, Bayan A. Mehdi, Wesal Fakhri Hassan, Muhanad Sabty

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
FundersUniversity of Basrah
KeywordsLegislationEnvironmental planningLawEnvironmental lawBusinessEnvironmental protectionPolitical scienceGeography

Abstract

fetched live from OpenAlex

The objective of this research is to address a gap in the existing literature by documenting the inadequate level of environmental awareness among diverse societal sectors and its detrimental effects on the environmental situation of Basrah Governorate, Southern Iraq.The current research examines the extent to which insufficient community awareness of Environmental Law No. 27 of 2009 contributes to the adverse environmental conditions in Basra Governorate.The results of this preliminary investigation indicated a widespread lack of awareness of environmental legislation across all societal sectors and the potential consequences of this lack of knowledge on environment-related attitudes and concerns among a statistically representative subset of the population.Principal component analysis (PCA) was used to analyze 309 responses to determine the association, similarity, and difference between responses to a series of questions.This survey revealed that people from all walks of life are not familiar with Iraqi Environmental Law.Moreover, the environmental concern was also found to be low.On the other hand, gender, social status, and educational level failed to provide consistent or conclusive results.

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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.332
Teacher spread0.293 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Sustainable Development and PlanningSame topicMiddle East and Rwanda ConflictsFrench-language works237,207