The Influence of Redistributive Politics on the Decision Making of Quasi-autonomous Organizations. The Case of<i>Infrastructures-Transport</i>(Quebec–Canada)
Bibliographic record
Abstract
This article presents the findings of a study on the influence of redistributive politics on grant distribution of a municipal infrastructure funding program managed by a quasi-autonomous organization. The study indicates that grant distribution among the municipalities is not exempt from redistributive politics. Municipalities located in swing districts and those represented by members from the party in power or by members having more seniority have a greater propensity to receive grants than other municipalities. The study thus casts doubt on one of the main claims of the proponents of quasi-autonomous organizations according to which the decision making of these bodies is exempt from partisan politics. Este artigo apresenta os resultados de um estudo sobre a influência de políticas redistributivas na distribuição de recursos de um programa municipal de financiamento de infraestrutura gerenciado por uma organização quase-autônoma. O estudo indica que a distribuição de recursos entre os municípios não é isenta de políticas de redistribuição. Municípios localizados em distritos onde ocorrem oscilações políticas e aqueles representados pelos membros do partido político no poder, ou por vereadores mais antigos, apresentam uma maior propensão a receber recursos do que outros municípios. O estudo, então, lança dúvida em uma das maiores reivindicações dos proponentes das organizações quase-autônomas, que seria o fato de que a tomada de decisão destes conselhos é isenta de partidarismo político. Translated by Ricardo Gomes, University of Brasília
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".