Dataset Information

Election turnout statistics in many countries: similarities, differences, and a diffusive field model for decision-making.

ABSTRACT: We study in details the turnout rate statistics for 77 elections in 11 different countries. We show that the empirical results established in a previous paper for French elections appear to hold much more generally. We find in particular that the spatial correlation of turnout rates decay logarithmically with distance in all cases. This result is quantitatively reproduced by a decision model that assumes that each voter makes his mind as a result of three influence terms: one totally idiosyncratic component, one city-specific term with short-ranged fluctuations in space, and one long-ranged correlated field which propagates diffusively in space. A detailed analysis reveals several interesting features: for example, different countries have different degrees of local heterogeneities and seem to be characterized by a different propensity for individuals to conform to the cultural norm. We furthermore find clear signs of herding (i.e., strongly correlated decisions at the individual level) in some countries, but not in others.

SUBMITTER: Borghesi C

PROVIDER: S-EPMC3354000 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Election turnout statistics in many countries: similarities, differences, and a diffusive field model for decision-making.

Borghesi Christian C Raynal Jean-Claude JC Bouchaud Jean-Philippe JP

PloS one 20120516 5

We study in details the turnout rate statistics for 77 elections in 11 different countries. We show that the empirical results established in a previous paper for French elections appear to hold much more generally. We find in particular that the spatial correlation of turnout rates decay logarithmically with distance in all cases. This result is quantitatively reproduced by a decision model that assumes that each voter makes his mind as a result of three influence terms: one totally idiosyncrat ...[more]

PMID: 22615762

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Project description:IntroductionDrugs for rare diseases (DRDs) offer important health benefits, but challenge traditional health technology assessment, reimbursement, and pricing processes due to limited effectiveness evidence. Recently, modified processes to address these challenges while improving patient access have been proposed in Canada. This review examined processes in 12 jurisdictions to develop recommendations for consideration during formal government-led multi-sectoral discussions currently taking place in Canada.Methods(i) A scoping review of DRD reimbursement processes, (ii) key informant interviews, (iii) a case study of evaluations for and the reimbursement status of a set of 7 DRDs, and (iv) a virtual, multi-stakeholder consultation retreat were conducted.ResultsOnly NHS England has a process specifically for DRDs, while Italy, Scotland, and Australia have modified processes for eligible DRDs. Almost all consider economic evaluations, budget impact analyses, and patient-reported outcomes; but less than half accept surrogate measures. Disease severity, lack of alternatives, therapeutic value, quality of evidence, and value for money are factors used in all decision-making process; only NICE England uses a cost-effectiveness threshold. Budget impact is considered in all jurisdictions except Sweden. In Italy, France, Germany, Spain, and the United Kingdom, specific factors are considered for DRDs. However, in all jurisdictions opportunities for clinician/patient input are the same as those for other drugs. Of the 7 DRDs included in the case study, the number that received a positive reimbursement recommendation was highest in Germany and France, followed by Spain and Italy. No relationship between recommendation type and specific elements of the pricing and reimbursement process was found.ConclusionsBased on the collective findings from all components of the project, seven recommendations for possible action in Canada are proposed. These focus on defining "appropriate access", determining when a "full" HTA may not be needed, improving coordination among stakeholder groups, developing a Canadian framework for Managed Access Plans, creating a pan-Canadian DRD/rare disease data infrastructure, genuine and continued engagement of patient groups and clinicians, and further research on different decision and financing options, including MAPs.

Project description:According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations.

Dataset Information

Election turnout statistics in many countries: similarities, differences, and a diffusive field model for decision-making.

Publications

Election turnout statistics in many countries: similarities, differences, and a diffusive field model for decision-making.

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