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Record W3049703644 · doi:10.4337/9781788976879.00012

Developing national scale integrated social-ecological scenarios for Canada’s oceans and marine fisheries

2020· book-chapter· en· W3049703644 on OpenAlexaboutno aff
Louise Teh, W.L. Cheung, U. Rashid Sumaila

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2020
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityFutures contractEnvironmental resource managementClimate changeArcticGeographyScale (ratio)Marine ecosystemFisheryEnvironmental planningEcosystemEcologyEnvironmental scienceBusiness

Abstract

fetched live from OpenAlex

Canada is surrounded by three social-ecologically distinct ocean regions: the Arctic, Atlantic and Pacific. These oceans support rich biodiversity and provide vital social, economic and cultural benefits to Canadian society. The long-term sustainability of Canadian oceans is challenged by uncertainty over the impacts of future climate and socio-economic change. Scenario analysis can be used to address this uncertainty by exploring alternative futures for Canada’s three oceans under different pathways of climate, economic development, social and policy changes. However, to date there has been no national-scale scenario developed to enable the investigation of Canada’s future ocean sustainability. To facilitate this process, the authors discuss whether existing scenarios of Canadian oceans provide an integrative, social-ecological perspective about potential future conditions for Canada’s fisheries and marine ecosystems. They then apply the findings to inform the development of a national-level scenario framework which allows a social-ecological examination of Canada’s oceans in terms of the state of future environmental, social and economic uncertainties.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.596
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.004
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 head0.023
GPT teacher head0.204
Teacher spread0.181 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

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