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Record W2115263081 · doi:10.1068/d0813

The Eco-Scalar Fix: Rescaling Environmental Governance and the Politics of Ecological Boundaries in Alberta, Canada

2013· article· en· W2115263081 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Planning D Society and Space · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversity of British ColumbiaAcadia University
Fundersnot available
KeywordsCorporate governanceFraming (construction)PoliticsEnvironmental governancePolitical ecologyExternalitySociologyNatural resourceEnvironmental ethicsEcologyEnvironmental resource managementPolitical scienceEconomicsGeographyLawManagement

Abstract

fetched live from OpenAlex

This paper engages with recent work in political ecology that explores the ways in which scale is imbricated in environmental governance. Specifically, we analyze the deployment of specific ecological scales as putatively ‘natural’ governance units in rescaling processes. To undertake this analysis, the paper brings two sets of literature into dialogue: (1) political ecology of scale and (2) political economy of rescaling, drawing on theories of uneven development. Building on this literature, we develop the concept of an ecoscalar fix and explore its analytical potential through a case study of the rescaling of water governance in Alberta, Canada. We argue that although the ‘eco-scalar fix’ is usually framed as an apolitical governance change—particularly through the framing of particular scales (ie, the watershed) as ‘natural’—it is often, in fact, a deeply political move that reconfigures power structures and prioritizes some resource uses over others in ways that can entrench, rather than resolve, the crises it was designed to address. Moreover, we suggest that, although watershed governance is often discursively depicted as an environmental strategy (eg, internalizing environmental externalities by aligning decision making with ecological boundaries), it is often articulated with—and undertaken to address challenges that arise through—processes of uneven development.

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 score0.249
Threshold uncertainty score0.947

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 studies0.0010.002
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 head0.004
GPT teacher head0.182
Teacher spread0.179 · 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