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Record W3096950292 · doi:10.5539/jms.v10n2p112

Sustainable Coastal Zone Management: Need for a Holistic Approach for Bangladesh

2020· article· en· W3096950292 on OpenAlexvenueno aff
Md Ataur Rahman Khan

Bibliographic record

VenueJournal of Management and Sustainability · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
FundersLiverpool Hope University
KeywordsStorm surgeCoastal managementCoastal zoneClimate changeLegislationSaltwater intrusionSustainable managementCoastal erosionMultidisciplinary approachEnvironmental planningEnvironmental resource managementHolistic managementSustainable developmentIntegrated coastal zone managementGeographyBusinessWater resource managementSustainabilityStormErosionEnvironmental scienceOceanographyEngineeringPolitical scienceAquiferGeologyGroundwaterMeteorologyEcology

Abstract

fetched live from OpenAlex

Coastal Zone is the most vulnerable area which is often attacked by cyclones, storm surges, floods, erosion and affected by climate change impacts like prolonged drought, salinity intrusion & greater temperature extremes. These realities are true both for the developed nations and a developing country like Bangladesh. This review study aims to explore the coastal management approaches in the UK & EU and the prevailing coastal management scenarios of Bangladesh. Based on the existing coastal management situations of Bangladesh, this study suggests that Bangladesh needs a holistic coastal management mechanism that should be supported by legislation, run by administrative and institutional frameworks, staffed by multidisciplinary experienced professionals under a Coastal Zone Management Authority (CZMA) for sustainable coastal zone management.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.229
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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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