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Record W2119673178 · doi:10.1177/1035304615574973

The privatisation of Australian electricity: Claims, myths and facts

2015· article· en· W2119673178 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Economic and Labour Relations Review · 2015
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
FundersAustralian Government
KeywordsLiberalizationGovernment (linguistics)ElectricityQuarter (Canadian coin)Market economyInvestment (military)BusinessEconomicsProject commissioningPrivate sectorMythologyValue (mathematics)FinanceCommercePublishingEconomic growthPoliticsLawEngineering

Abstract

fetched live from OpenAlex

Abstract Australia has one of the most ‘liberalised’ electricity sectors in the world. The sale of government-owned electricity companies has contributed to that liberalisation and a quarter of the proceeds of one of the world’s largest privatisation programmes. In 2014, the state governments of New South Wales and Queensland announced further electricity privatisations if re-elected. Advocates claim private ownership will mean more productive investment, lower costs leading to more efficient operations, lower prices for all consumers and better market functioning without government interference. Opponents contend that the true value of government businesses is not being realised at sale, retention can achieve returns greater than those from a sale, and that follow sale, prices will rise and jobs will be lost. This article demonstrates that the claims of either lower or higher prices, of job losses and of more efficient operations are tantamount to being myths of privatisation not borne out by reality.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.678
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.230
Teacher spread0.213 · 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