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Record W3186080151

Habitat Recovery in the Salish Sea, One Community at a Time: Community engagement for socio-ecological resilience of coastal restoration projects

2020· article· en· W3186080151 on OpenAlexaboutno aff
A. M. K. Mohana Rao

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
Fundersnot available
KeywordsResilience (materials science)Restoration ecologyHabitatCommunity resiliencePsychological resilienceGeographyEnvironmental resource managementEcologyEcological resilienceCommunityEnvironmental planningEnvironmental scienceEcosystemBiologyPsychologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Community engagement builds both social and ecological resilience of restoration projects. This is particularly true in coastal areas, which are complex both ecologically and socially. The Salish Sea Nearshore Habitat Recovery Program builds on 20 years of community building towards coastal ecosystem restoration on the south coast of British Columbia, Canada. Funding was obtained by a small non-profit organization for seagrass and marine riparian restoration, and marine debris removal to support forage fish and juvenile salmon habitat recovery. The engagement and involvement of a broad community including Indigenous groups, coastal residents, all levels of government, academics and industry has resulted in the equivalent of tens of thousands of dollars of additional support for restoration works within this program. The broader community is engaged in multiple steps of restoration including site selection, planning and implementation. Recognition of the value of traditional and local knowledge, an investment in bringing people together and ongoing communication have built collective enthusiasm and ownership over the project. Marrying restoration activities with cultural events is increasing ecological literacy and building the resilience of the work. Restoring or establishing connections between parties that do not otherwise work together is a fundamental step towards restoring ecosystems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.235
Teacher spread0.172 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

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