MétaCan
Menu
Back to cohort
Record W4212784852 · doi:10.1080/09644016.2022.2044219

Proxy-led accountability for natural resource extraction in rentier states

2022· article· en· W4212784852 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

VenueEnvironmental Politics · 2022
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAccountabilityNatural resourceConceptualizationDemocracyResource curseProxy (statistics)Economic rentPoliticsEconomicsBusinessPolitical economyPolitical scienceMarket economyLaw

Abstract

fetched live from OpenAlex

The resource curse literature suggests that, in fragile states dependent on natural resource rents, structures of public accountability are weak because of an elite-controlled political economy indifferent to social and ecological interests. We examine accountability claims made by non-domestic proxy actors, holding governments and corporations accountable on behalf of communities adversely affected by natural resources extraction. This conceptualization is suggested by proxy-led transnational mobilization against mining-related damage in the Democratic Republic of the Congo. We identify an ‘hourglass’ structure of proxy actor engagement with affected communities: In a first phase, proxies rely on public mechanisms to define standards remotely. In a second phase, proxies ‘narrow’ the gap by seeking compliance information from affected communities. However, in a third phase, this gap ‘widens’ again when proxies remotely seek sanctions against responsible actors. We discuss the applicability of this heuristic framework to proxy-led accountability practices in other natural resource-dependent rentier states.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.472

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 science0.0000.000
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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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