MétaCan
Menu
Back to cohort
Record W4386384326 · doi:10.32435/envsmoke-2023-0011

THE AWARENESS AND UNDERSTANDING OF ENVIRONMENTAL DEGRADATION IN DHAKA (BANGLADESH) URBAN AREA: A GENDER PERSPECTIVE

2023· article· en· W4386384326 on OpenAlexaff
Pinki Shah, U. Sumaiya

Bibliographic record

VenueENVIRONMENTAL SMOKE · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsEnvironmental degradationPerspective (graphical)GeographyEnvironmental pollutionEnvironmental planningDiversity (politics)PopulationEconomic growthSocioeconomicsSustainable developmentPopulation growthEnvironmental protectionEnvironmental healthPolitical scienceSociologyEcologyMedicine

Abstract

fetched live from OpenAlex

Growth efforts and the growing population have been creating an adverse impact on our bio-diversity therefore human health is at higher risk, and human civilization came closer to a severe Environmental crisis. Impacts of environmental degradation especially of air and water pollution have been severe and challenging in Bangladesh, and generally, city dwellers face higher pollution levels than rural residents in their everyday lives. The broad aim of this study is to assess the environmental awareness level of the population of Dhaka city. Based on both primary and secondary data, the study reveals a huge lack of awareness of environmental challenges and the necessity of handling these concerns with appropriate initiatives. Gender perspective reveals women’s potential areas of contribution to handling environmental challenges. Both men and women need to be brought under strategic environmental awareness and education programs for sustainable and healthy urban life in Bangladesh, the study concludes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.262
Teacher spread0.228 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueENVIRONMENTAL SMOKESame topicEnvironmental Education and SustainabilityFrench-language works237,207