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An Unequal Partnership: The Privatisation of Information Technology in Ontario

2015· article· en· W2661442949 on OpenAlexaboutno aff
David Rapaport

Bibliographic record

VenueWork Organisation Labour & Globalisation · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipOutsourcingCommodificationBusinessPaymentOpposition (politics)IdeologyGovernment (linguistics)State (computer science)Private sectorEconomicsPublic administrationPublic relationsMarket economyFinanceMarketingEconomic growthPolitical sciencePolitics

Abstract

fetched live from OpenAlex

This paper presents a case study of the outsourcing of IT services between 1996 and 2003 by the Government of Ontario using a Public Private Partnership (P3) as an example of the commodification of public services including the impact on labour. It argues that three key features of the arrangement led to it becoming an ‘unequal partnership.’ First, ideological notions of a ‘knowledge economy’ and the techno-wizard status of independent IT workers were used by IT corporations to charge very high corporate rates for the time of outsourced IT staff, despite the fact that they were in fact undergoing a process of proletarianisation. Second, the P3 cost-benefit structure of shared costs and shared payments provided the framework for corporate partners to realise higher profits from investment in privatised state activities. Third, the explicit support of influential state and near-state actors undermined opposition to P3 projects.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.630

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0260.014
Scholarly communication0.0050.003
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.285
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

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 designNot applicable
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

Citations0
Published2015
Admission routes1
Has abstractyes

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