MétaCan
Menu
Back to cohort
Record W2064560006 · doi:10.1080/15239080802332026

Power, Knowledge, and Public Engagement: Constructing ‘Citizenship’ in Alberta's Industrial Heartland

2008· article· en· W2064560006 on OpenAlexafffundabout
Jeffrey R. Masuda, Tara K. McGee, Theresa Garvin

Bibliographic record

VenueJournal of Environmental Policy & Planning · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicFoucault, Power, and Ethics
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersAlberta Innovates - Health Solutions
KeywordsGovernmentalityCitizenshipPublic participationPrivilege (computing)Corporate governancePublic relationsPublic engagementStakeholderStakeholder engagementPower (physics)SociologyPolitical sciencePublic administrationCivic engagementDemocracyDeliberative democracyPoliticsLawEconomicsManagement

Abstract

fetched live from OpenAlex

Foucault's concept of governmentality has provided the basis for recent analysis of governance that explains the connections between power and knowledge in the formation of subjects in advanced liberal societies. In this paper, we apply this concept to help to understand the persistent conflict and power struggles that are characteristic of contemporary public engagement in environmental planning, using the case study of a regional land use plan known as Alberta's Industrial Heartland. Drawing on document and media analysis and key stakeholder interviews carried out between 2002 and 2003, we describe how several ‘technologies of citizenship’ were deployed and ultimately resisted in a public engagement program that attempted to prescribe the terms of reference for public participation. The findings support a view that sees public engagement less as a tool for promoting democratic consensus and more as means to legitimate particular forms of governance that privilege narrowly defined economic goals at the expense of citizen rights and values.

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)0.004
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0220.044
Scholarly communication0.0100.003
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.081
GPT teacher head0.338
Teacher spread0.257 · 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

Citations44
Published2008
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Environmental Policy & PlanningSame topicFoucault, Power, and EthicsFrench-language works237,207