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Social Synergies, Tradeoffs, and Equity in Marine Conservation Impacts

2019· article· en· W2962921131 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Environment and Resources · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychological interventionEquity (law)Environmental resource managementCounterfactual thinkingPublic economicsMarine protected areaIntergenerational equitySocial equalityEnvironmental planningGeographyPolitical scienceEconomicsSustainabilityEcologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

Biodiversity conservation interventions often aim to benefit both nature and people; however, the social impacts of these interventions remain poorly understood. We reviewed recent literature on the social impacts of four marine conservation interventions to understand the synergies, tradeoffs, and equity (STE) of these impacts, focusing on the direction, magnitude, and distribution of impacts across domains of human wellbeing and across spatial, temporal, and social scales. STE literature has increased dramatically since 2000, particularly for marine protected areas (MPAs), but remains limited. Few studies use rigorous counterfactual study designs, and significant research gaps remain regarding specific wellbeing domains (culture, education), social groups (gender, age, ethnic groups), and impacts over time. Practitioners and researchers should recognize the role of shifting property rights, power asymmetries, individual capabilities, and resource dependency in shaping STE in conservation outcomes, and utilize multi-consequential frameworks to support the wellbeing of vulnerable and marginalized groups.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.511

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 communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.012
GPT teacher head0.255
Teacher spread0.243 · 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