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Record W2560028625 · doi:10.1080/14693062.2016.1242055

Mainstreaming climate change adaptation into inland aquaculture policies in Thailand

2016· article· en· W2560028625 on OpenAlexfundno aff
Anuwat Uppanunchai, Chanagun Chitmanat, Louis Lebel

Bibliographic record

VenueClimate Policy · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsZoningClimate changeEnvironmental resource managementEnvironmental planningBusinessSustainabilityGovernment (linguistics)Climate change mitigationNatural resource economicsGeographyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

While there have been many pilot projects on adaptation undertaken in the fisheries and aquaculture sector, state policies are only just beginning to address let alone refer to climate change. This study explores the climate-related content, climate sensitivities, and opportunities to incorporate climate change concerns in a set of aquaculture policies by the government of Thailand. The analysis is based on content analysis of policy documents and in-depth interviews with 14 officials that had roles in the design or implementation of 8 Department of Fisheries policies. The Aquaculture Master Plan 2011–2016 and the now abandoned Tilapia Strategy refer directly to climate variability or change. The Master Plan also suggests measures or strategies, such as investment in research, and the transfer of technologies, which would be helpful to sustainability and adaptation. Other policies suggest, or at the very least include, practices which could contribute to strengthening management of climate-related risks, for example: a registration policy included provisions for compensation; extension programme policy recognizes the importance of extreme events; and a standards policy gives guidance on site selection and water management. Most existing aquaculture policies appear to be sensitive to the impacts of climate change; for instance, the zoning policy is sensitive to spatial shifts in climate. Stakeholders had ideas on how policies could be made more robust; in the case of zoning, by periodically reviewing boundaries and adjusting them as necessary.POLICY RELEVANCEThis study is one of the first evaluations of the coverage and sensitivity of aquaculture policies to climate change. It shows that while existing policies in Thailand are beginning to refer explicitly to climate change, they do not yet include much in the way of adaptation responses, underlining the need for identifying entry points as has been done in this analysis. Further mainstreaming is one option; another possibility is to adopt a more segregated approach, at least initially, and to collect various policy ideas under a new strategic policy for the aquaculture sector as a whole.

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)0.009
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.002
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 head0.019
GPT teacher head0.255
Teacher spread0.236 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

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