MétaCan
Menu
Back to cohort
Record W2084437446 · doi:10.1080/00049180902964934

Political Geographies of Lobbying: Canberra within Australian politics

2009· article· en· W2084437446 on OpenAlexaboutno aff
Chris Beer

Bibliographic record

VenueAustralian Geographer · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsMarketing buzzPolityPoliticsSituatedGovernment (linguistics)SociologyMetisMedia studiesPolitical geographyPolitical sciencePublic administrationLawAdvertisingBusiness

Abstract

fetched live from OpenAlex

This paper seeks to examine the ambiguous place of Canberra within the political geography of Australia, through exploring the place of the city among a particular category of political actors—lobbyists. Drawing on a series of interviews with lobbyists working for interest groups, government relations firms, or as freelancers, the city is presented as a central site of lobbying within the national polity through two key (and related) dimensions: the city as a site of localised political knowledge, or metis; and Canberra as a place of ‘urban buzz’ or situated communicative interaction. The paper concludes both with a discussion of how these concepts may help us to better understand the political behaviours of lobbyists, and how the observed spatial imaginations and practice of lobbyists in Canberra interacts with the theorisation of ‘urban buzz’.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0100.013
Scholarly communication0.0070.003
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.048
GPT teacher head0.319
Teacher spread0.270 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAustralian GeographerSame topicCultural Industries and Urban DevelopmentFrench-language works237,207