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Record W6998480705

Addressing Human Dimensions within the criteria for conservation and sustainable use of Ramsar Wetlands

2023· dissertation· en· W6998480705 on OpenAlexafffund

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsWetlandRamsar siteLivelihoodSustainabilityEcosystem servicesWetland conservationVulnerability (computing)Government (linguistics)Sustainable development
DOInot available

Abstract

fetched live from OpenAlex

Wetlands are unique ecosystems that provide many direct and indirect services to the human population. Several policy frameworks have been developed and implemented at various levels of government worldwide to address the social, environmental and economic consequences of the loss of wetland services. These frameworks have varying degrees of flexibility to balance the need to protect remaining wetlands and pursue economic development. Therefore, this research addresses the importance of considering human dimension criteria on the International Conservation and Wetlands Ramsar Site to encourage local policy maker to understand the binding effect of decision-making and governance of wetlands in their countries on local coastal community and international socio-economy for sustainable wetland and increase of livelihood of dependence community. The finding of this research addresses the importance of human relations with wetlands sustainability and community economic survival. It suggests the importance of considering the human dimension in the International Wetland Ramsar Site based on the findings in this research. This research analyzes pathways of vulnerability resulting from mismanagement and the effect of policies and governance; in general, and the case study area of the Chilika Lagoon, the largest coastal Lagoon on the east coast of India and the lifeline of the state of Odisha as an example to show the importance of addressing human dimension and its effect on survival of local and international wetland. This research examines and analyses the critical elements of the social well-being of coastal communities and reviews the ecosystem services of wetlands suggested on the Ramsar Site and other academic works of literature to make a linkage between the two elements and the direct and indirect impacts of natural and anthropogenic factors that have profoundly affected the vulnerable coastal community’s socio-economy and wetland sustainability and survival. Overall, the research addresses the sustainable management of coastal communities of SSFs by providing details on how fisher vulnerability may be closely linked to wetland management and governance and its related impacts. Further, the research provides some answers to how SSF viability can be achieved through coping and adaptive responses by small-scale fishing communities to the changes in local and international wetland management. The results of this thesis indicated that improving the social well-being of coastal communities could provide valuable insights to achieve improved control of food and fisheries resources. The result of this study will imply the importance of addressing Human Dimension criteria on the International Ramsar Site as one of the essential criteria next to the nine ecological base criteria on the Site to suggest more sustainable wetlands on the local and international level and improve the socio-economy of the costa community as they are connected.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.033
GPT teacher head0.245
Teacher spread0.213 · 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 designQualitative
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 routes2
Has abstractyes

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