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Le transport ferroviaire régional de voyageurs en France : à la lumière de la théorie néo-institutionnaliste et des comptes de surplus

2010· dissertation· en· W23555814 on OpenAlexfundno aff
Christian Desmaris

Bibliographic record

VenuePLoS ONE · 2010
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

This thesis, which fits the general economic issues on the research tools of regulation of network industries, questions the appropriateness of regionalization of French railways. The latter, since the reform introduced by Law SRU associates maintain the monopoly to operate the railway service for Transport Express Regional (TER) with decentralization to the regions of a prerogative hitherto ensured bureaucratic and centralized. In this institutional environment, original in comparison with the European movement, the French regions have they managed to write and to govern the "system SNCF-TER” ? To answer these two questions, the author engages the neo-institutional theory, from which it offers an array of interpretive economic architecture conventions TER and a transposition of this method accounts surplus (MAS) for study the economic performance of these contracts. The results obtained on the sample of seven regions that have experienced the regionalization can only partially confirm the usual deductions made from the standard theory of monopoly and capture the regulator by the regulated firm. If the contracting SNCF / regions far removed from the model "net cost", expresses the acceptance by the legislature of a broad insurance cover industrial, commercial, and more on investments by the Community, regionalization resulted a variety of employment contracts. A detailed analysis shows the hybrid modes of governance that the author calls "fiduciaro-authoritarian". The MAS found that while the effect of monopoly is present and needed to Regions, it does little to benefit the railway operator, but rather to RFF. The trend, travelers have become "winners" of regionalization rail.

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)0.001
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicTransport and Economic PoliciesFrench-language works237,207