MétaCan
Menu
Back to cohort
Record W2159195187 · doi:10.5751/es-06381-190274

Integrating adaptive governance and participatory multicriteria methods: a framework for climate adaptation governance

2014· article· en· W2159195187 on OpenAlexvenueno aff
Stefania Munaretto, Giuseppina Siciliano, Margherita Turvani

Bibliographic record

VenueEcology and Society · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceAdaptation (eye)Citizen journalismEnvironmental resource managementClimate change adaptationClimate changeEnvironmental governanceClimate governanceMulti-level governanceEnvironmental planningAdaptive capacityBusinessPolitical scienceGeographyEcologyEconomicsPsychologyBiology

Abstract

fetched live from OpenAlex

S. Munaretto, G. Siciliano, and M. E. Turvani. 2014. Integrating adaptive governance and participatory multicriteria methods: a framework for climate adaptation governance. Ecology and Society 19(2): 74. https://doi.org/10.5751/ES-06381-190274

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)0.167
metaresearch head score (Gemma)0.132
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.167
Threshold uncertainty score0.885

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1670.132
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.006
Science and technology studies0.0050.023
Scholarly communication0.0110.010
Open science0.0050.015
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0060.001

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 head0.054
GPT teacher head0.338
Teacher spread0.284 · 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 designTheoretical or conceptual
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

Citations95
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEcology and SocietySame topicUrban Planning and ValuationFrench-language works237,207