MétaCan
Menu
Back to cohort
Record W1952933116 · doi:10.18352/ijc.318

Levels, scales, linkages, and other 'multiples' affecting natural resources

2012· article· en· W1952933116 on OpenAlex
Amy R. Poteete

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

VenueInternational Journal of the Commons · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsMultipleFraming (construction)Computer scienceEconometricsEnvironmental resource managementEconomicsGeographyMathematics

Abstract

fetched live from OpenAlex

Natural resources are affected by several types of “multiples.” Some analysts emphasize linkages across multiple scales while others focus on interactions across multi-level institutions or multiple fields of action. Different ways of framing the “multiples” associated with socio-ecological systems are important because they influence what analysts see – and do <em>not</em> see. Given the complexity of these systems, a narrow frame of analysis increases the risk that critical issues will be overlooked. Framing analysis in terms of “multi-dimensional linkages” – including multiple scales, multi-level institutions, and other types of multiples – reduces that risk by directing attention to a broader range of factors, processes, and interactions.

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 score0.131
Threshold uncertainty score0.177

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 head0.023
GPT teacher head0.241
Teacher spread0.218 · 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