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Record W3137396517 · doi:10.21810/strm.v7i2.129

Neoliberalism, P3s, and the Canadian Municipal Water Sector

2016· article· en· W3137396517 on OpenAlexaffvenueabout
Michael Lang

Bibliographic record

VenueStream Interdisciplinary Journal of Communication · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTechnocracyPublic administrationNeoliberalism (international relations)PoliticsAusterityAccountabilityCorporate governancePolitical scienceBusinessFinanceLaw

Abstract

fetched live from OpenAlex

In this paper I consider how the increase of Public-Private Partnerships (P3s) in Canada now threatens the autonomy of municipal water services. P3s have gained traction since the 1990s as a mechanism of private alternative service delivery that replace traditional public provision. Over the past decade, P3s have been actively promoted by the state via quasi-government agencies such as Public-Private Partnerships Canada (PPP Canada), yet their results have been markedly poor. Nevertheless, P3s are now being situated as a key mechanism in the neoliberal (re)regulation of public services, regardless of their shortcomings and inequities. With this in mind, I frame recent Federal policy changes concerning the funding of local water infrastructure and services and their implementation through such agencies as PPP Canada as expressions of post-political governance in Canada. I argue that the capacity for local decision-making concerning this integral social and ecological service is being overwhelmed by a technocratic, expert-driven political process that is contingent on the hegemony of economic austerity to institute municipal water privatization, free from democratic accountability.
 
 
 
 
 
 
 
 
 
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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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.167
Threshold uncertainty score0.966

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0190.029
Scholarly communication0.0100.003
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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

Citations3
Published2016
Admission routes3
Has abstractyes

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