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Record W2027012313 · doi:10.1177/0309132510380488

Small technologies, big change: Rethinking infrastructure through STS and geography

2010· article· en· W2027012313 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProgress in Human Geography · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversité de Montréal
FundersInfrastructure CanadaCanadian Water NetworkUniversity of ManchesterStockholm Environment Institute
KeywordsMalleabilityEconomic geographyHuman geographyActor–network theoryTime geographySociologyPolitical scienceGeographyDevelopment geographyHistorical geographySocial scienceComputer scienceComputer security

Abstract

fetched live from OpenAlex

Infrastructure tends to be conceived as stabilized and ‘black-boxed’ with little interaction from users. This fixity is in flux in ways not yet fully considered in either geography or science and technology studies (STS). Driven by environmental and economic concerns, water utilities are increasingly introducing efficiency technologies into infrastructure networks. These, I argue, serve as ‘mediating technologies’ shifting long-accepted socio-technical and environmental relationships in cities. The essay argues for a new approach to infrastructure that, by integrating insights from STS and geography, highlights its malleability and offers conceptual tools to consider how this malleability might be fostered.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.030
GPT teacher head0.288
Teacher spread0.259 · 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