MétaCan
Menu
Back to cohort
Record W7110806220 · doi:10.1016/j.esg.2025.100306

Horizontal venue-shopping and non-governmental organizations’ influence on regional fisheries management organizations

2025· article· en· W7110806220 on OpenAlexfundno aff

Bibliographic record

VenueEarth System Governance · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNippon FoundationUniversity of British ColumbiaStiftelsen för Miljöstrategisk Forskning
KeywordsCorporate governanceContext (archaeology)Horizontal and verticalCommissionFisheries managementArgument (complex analysis)Marine protected areaPreference

Abstract

fetched live from OpenAlex

The influence of non-governmental organizations (NGOs) on international organizations is a perennial question in global governance research. We examine whether and why horizontal venue-shopping strengthens NGO influence on international organizations in the area of biodiversity protection. We argue that horizontal venue-shopping facilitates NGO influence, building on previous studies on institutional complexity and NGO influence in global governance. The argument is examined through process tracing based on extensive fieldwork material in the context of the governance of sharks in the International Commission for the Conservation of Atlantic Tunas during 1994–2021. We find NGO preference attainment in a majority of the studied policy processes, and indicative evidence of increased NGO influence over time. The results suggest that horizontal venue-shopping strengthened the influence of NGOs in several of the examined processes. These findings have broader implications for research on NGO influence in an increasingly complex global governance landscape.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEarth System GovernanceSame topicMarine and fisheries researchFrench-language works237,207