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Record W2897027017 · doi:10.1177/0263774x18802954

The <i>terroir</i> of bureaucratic practice: Everyday life and scholarly method in the study of policy

2018· article· en· W2897027017 on OpenAlex
Merje Kuus

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironment and Planning C Politics and Space · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaConcordia UniversityCardiff University
KeywordsBureaucracyPoliticsScholarshipEveryday lifeEuropean unionArticulation (sociology)SociologyPolitical scienceSocial scienceLawEconomics

Abstract

fetched live from OpenAlex

This article seeks to connect political geographic scholarship on institutions and policy more firmly to the experience of everyday life. Empirically, I foreground the ambiguous and indeterminate character of institutional decision-making and I underscore the need to closely consider the sensory texture of place and milieu in our analyses of it. My examples come from the study of diplomatic practice in Brussels, the capital of the European Union. Conceptually and methodologically, I use these examples to accentuate lived experience as an essential part of research, especially in the seemingly dry bureaucratic settings. I do so in particular through engaging with the work of Michel de Certeau, whose ideas enjoy considerable traction in cultural geography but are seldom used in political geography and policy studies. An accent on the texture and feel of policy practice necessarily highlights the role of place in that practice. This, in turn, may help us with communicating geographical research beyond our own discipline.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.026
GPT teacher head0.338
Teacher spread0.312 · 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