Exercising knowledge of costs: behavioural politics of economic restraint in French public service reform

Alauzen, Marie; Muniesa, Fabián; Violle, Alexandre

doi:10.1057/s41253-020-00131-9

Cited by 5 publications

(2 citation statements)

References 40 publications

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“…In addition, there are two main types of sports organizations that exist in society: administrative and public service. From the experience of community sports construction in developed countries, the funding for community sports mainly comes from government input, but families, enterprises, lotteries, and other channels are also gradually becoming important sources [11][12][13][14].…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

Dang

Liu

et al. 2021

Computational Intelligence and Neuroscience

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In this paper, a deep confidence neural network algorithm is used to design and deeply analyze the risk warning model for stadium operation. Many factors, such as video shooting angle, background brightness, diversity of features, and the relationship between human behaviors, make feature attribute-based behavior detection a focus of researchers’ attention. To address these factors, researchers have proposed a method to extract human behavior skeleton and optical flow feature information from videos. The key of the deep confidence neural network-based recognition method is the extraction of the human skeleton, which extracts the skeleton sequence of human behavior from a surveillance video, where each frame of the skeleton contains 18 joints of the human skeleton and the confidence value estimated for each frame of the skeleton, and builds a deep confidence neural network model to classify the dangerous behavior based on the obtained skeleton feature information combined with the time vector in the skeleton sequence and determine the danger level of the behavior by setting the corresponding threshold value. The deep confidence neural network uses different feature information compared with the spatiotemporal graph convolutional network. The deep confidence neural network establishes the deep confidence neural network model based on the human optical flow information, combined with the temporal relational inference of video frames. The key of the temporal relationship network-based recognition method is to extract some frames from the video in an orderly or random way into the temporal relationship network. In this paper, we use several methods for comparison experiments, and the results show that the recognition method based on skeleton and optical flow features is significantly better than the algorithm of manual feature extraction.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

Dang

Liu

et al. 2021

Computational Intelligence and Neuroscience

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show abstract

“…À la sortie de l'hôpital, les soignants n'indiquent pas nécessairement aux patients de passer par la caisse et la majorité des « factures » 6 , bien que d'un montant faible pour le patient (17,2 € en moyenne), ne sont jamais honorées. Dans un contexte de recherche d'efficience et de sécurisation des recettes caractérisée par la multiplication des exercices de connaissance des coûts (Alauzen et al, 2020), la DGOS a donné pour mission au SGMAP d'aider les établissements de santé à rénover la chaîne de facturation, à mieux recouvrir le paiement des actes de soin et à formaliser les parcours administratifs dans les établissements. Après la construction de parcours suivant des méthodes bien ancrées au SGMAP (Gélédan, 2016), la direction générale des finances publiques a établi une première maquette standardisée de l'« avis des sommes à payer », soit la facture que l'hôpital adresse au bénéficiaire des soins (Fig.…”

Section: Classification Des Interventions (2014-2019)unclassified

Le design est-il en passe de devenir une science de gouvernement ? Réflexion sur les espoirs suscités par les sciences du design dans la modernisation de l’État en France (2014–2019)

Alauzen¹,

Malivel²

2020

Sciences Du Design

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Le design est-il en passe de devenir une science de gouvernement ?Réflexion sur les espoirs suscités par les sciences du design dans la modernisation de l'État (2014-2018) Marie Alauzen et Coline Malivel Résumé : Constatant le rôle pris ces dernières années en France par le design dans la modernisation de l'État, nous nous demandons si ce dernier ne serait pas en passe de devenir une science de gouvernement au même titre que la statistique, la cartographie, la criminologie, l'archivistique, l'économie politique ou encore les études d'opinion. L'article s'inscrit dans la continuité de réflexions récentes en histoire des sciences du design et de questionnements politiques plus anciens sur les sciences de gouvernement des États modernes. En revenant sur l'incorporation du design par l'administration française de la modernisation de l'État entre 2014 et 2019, il propose une mise en ordre des interventions menées, ainsi que des espoirs et frustrations suscités par l'avènement du design en administration.Mots clés : sciences de gouvernement, histoire des sciences, modernisation de l'État, sciences du design Abstract: The article questions the role that design has played in recent years in the modernization of the state in France. We wonder if it is not becoming a science of government in the same way as statistics, cartography, criminology, archival science, political economy or opinion studies did. It is drawing on some recent debates in the history of design sciences and of older political ones on the sciences of government of modern states. Returning to the incorporation of design by the French administration of the modernization of the State between 2014 and 2019, it gives an order to the implementations carried out as well as hopes and frustrations raised by the advent of design in public administrations.

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Conventions of the State, Statistics, and Public Action in a Territorial Perspective

Bartl

2023

Handbook of Economics and Sociology of Conventions

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Exercising knowledge of costs: behavioural politics of economic restraint in French public service reform

Cited by 5 publications

References 40 publications

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

Le design est-il en passe de devenir une science de gouvernement ? Réflexion sur les espoirs suscités par les sciences du design dans la modernisation de l’État en France (2014–2019)

Conventions of the State, Statistics, and Public Action in a Territorial Perspective

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