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Record W7056585351

Gouvernance et imputabilité : la protection des valeurs publiques à l'ère de la privatisation des services d'eau

2003· dissertation· fr· W7056585351 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2003
Typedissertation
Languagefr
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Perspective (graphical)Corporate governanceWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

The international year of fresh water represents the opportunity to look back at the seemingly irresistible movement toward privatization and at the devolution of State responsibilities in water and wastewater services. The welfare State appears to be increasingly ill-adapted to times dominated by globalisation and efficiency, while the market and the private corporations are presented as a panacea for solving the water crisis. But expectations of the market have not been met. This thesis analyses the debate over privatization of these services and the fondamental impacts on public values of introducing a market philosophy into this industry. Rather than witnessing a retreat of the State, its role is evolving although direct service provision is superseded by heavy regulation of the industry. In criticizing the neoclassical approach to the public good and regulation, the thesis argues that individualizing the process of valuing the public good fosters a culture of conflict and complexity that ultimately undermines our ability to formulate and achieve common goals. This creates an important accountability deficit. The need for environmental efficiency and democracy in an era of uncertainty requires that we search for means of expanding the reach of public values and thus suggests an even deeper reshaping of our governance structures, public and private.

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)0.005
metaresearch head score (Gemma)0.021
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 score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.006
Scholarly communication0.0130.006
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0360.006

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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