Non-experts’ participation in processes of scientific knowledge creation: The case of Citizen Science

Public participation in science and technology, is currently being encouraged in order to fulfil the calls for a more engaging, transparent, and ethical way of governing technoscientific innovation. Several institutional documents argue for the need to enrol non-scientists into research programs; funding schemes devoted to public engagement seem to be paving the way for new baselines for knowledge creation and innovation paths that include the contributions of citizens. Citizen Science stands out as an opportune movement to lead non-scientists to contribute to scientific research projects and technological innovation, and it has given rise to a broad debate intersecting many sociological aspects linked to participation and community empowerment. However, the participation of non-scientists in data collection, analysis, and interpretation is not totally new; yet it has not had the same value across time, nor has it always been considered desirable. Indeed, volunteers' engagement and amateurs' contributions have been regulated differently compared to the current rhetoric of participation. This paper gives an account of the evolution of participation of non-experts through the lens of Science and Technology Studies, investigating its desirability, how it is governed, and whether it matches the promises of Citizen Science practitioners.     

Robust winner determination in positional scoring rules with uncertain weights

Theory and Decision - Scoring rules constitute a particularly popular technique for aggregating a set of rankings. However, setting the weights associated with rank positions is a crucial task, as...     

Measuring Health Inequality in US: A Composite Index Approach

Social Indicators Research - In this paper, we use the standardized mortality rates for 21 mutual exclusive causes of death to propose a composite index of US county-level health performances in...     

Validity and reliability of the Italian Gambling Functional Assessment–Revised

Problem gambling is a growing phenomenon in Italy, and there is increasing interest in studying the reasons for gambling in the Italian community. The Gambling Functional Assessment–Revised (GFA-R) was developed to assess two contingencies maintaining gambling behaviour: positive reinforcement and escape. The study hypothesized that the GFA-R could be translated and adopted in the Italian context. The main purpose of this study was to test the factor structure of the Italian version of the GFA-R by means of confirmatory factor analysis, its internal consistency and validity, in a sample of 667 Italian-speaking adults, recruited at universities, banks, of?ces, industries, markets, public parks and shops in five regions: Piemonte, Veneto, Lazio, Calabria and Puglia. The study found that the scale was internally consistent, and results showed that the original two-factor model fitted the data well. It also found moderate correlations between the GFA-R-I and both SOGS scores and GRCS scores. These results will allow Italian psychologists, educators and policymakers to identify specific contingencies maintaining gambling behaviour (positive reinforcement vs. escape) in the Italian community, detecting people more at risk of developing disordered gambling, with significant improvements in terms of prevention and clinical intervention.     

Valori e norme di fronte alla complessità

Riassunto

Scopo del presente contributo è quello di evidenziare alcune connessioni concettuali fra il mondo normativo ed il moderno approccio della complessità.

A partire dal 1972, psicologi, etologi, antropologi culturali hanno sottolineato l'importanza dei codici sociali—oggettivati in diritti e doveri—in quanto parte integrante della interazione sociale. In particolare Calegari e Massimini (1979) hanno sostenuto che Le Costituzioni possono essere analizzate quali organizzazioni gerarchiche di sistemi complessi. Gli autori hanno indicato—nell'ambito di sistemi normativi—delle gerarchie di comprensione e di connessione riferite a centri di controllo di comportamenti registrati nelle Leggi fondamentali. Essi hanno sviluppato un metodo di analisi basato sulla identificazione di unità molari e di loro relazioni ed hanno messo a punto una serie di indici utili a misurare le dimensoni di complessità di tali sistemi.

Sulla base di un sucessivo approfondimento, l'autore ha centrato la sua attenzione sulle decisioni adattive incluse nelle Costituzioni. La conseguente analisi cognitiva mostra che le strategie normative si configurano in livelli (metapiani, piani globali, sottopiani, istruzioni comportamentali) in accordo con la ipotesi sistémica generale formulata da Bruner, Goodnow ed Austin (1966). La organizzazione gerarchica di questo tipo di strategia è caratterizzata dalla valenza e dalla covalenza di piani globali e di sottopiani, dal grado di similarità dei metapiani e dei piani globali, dal grado di ridondanza emergente ai differenti livelli gerarchici.

Le decisioni adattive sono presenti in numero limitato e ciò conferma le stipulazioni formulate dagli antropologi culturali. L'autore sottolinea che la presenza di ridondanza negli elementi di un sistema complesso rende possibile la sua descrizione in modo più coerente e completo.     

LR cointegration tests when some cointegrating relations are known

This paper considers the asymptotic analysis of the likelihood ratio (LR), cointegration (CI) rank test in vector autoregressive models (VAR) when some CI vectors are known and fixed. It is shown that the limit law is free of nuisance parameters. In the case of LR tests against the alternative of completely unrestricted CI space, the limit law can be expressed as the convolution of known distributions. This deconvolution is employed to approximate the quantiles of the distribution, without resorting to new simulations.     

Statistical models for e-learning data

In this paper we analyse a real e-learning dataset derived from the e-learning platform of the University of Pavia. The dataset concerns an online learning environment with in-depth teaching materials. The main focus of this paper is to supply a measure of the relative importance of the exercises (test) at the end of each training unit; to build predictive models of student’s performance and finally to personalize the e-learning platform. The methodology employed is based on nonparametric statistical methods for kernel density estimation and generalized linear models and generalized additive models for predictive purposes.     

A fuzzy logic approach to poverty analysis based on the Gini and Bonferroni inequality indices

In the poverty analysis framework, a great deal of attention has been paid to the poverty measurement in terms of monetary variables, such as income or consumption. In this context, a relevant open problem is connected with the distinction between poor and non-poor. In fact, the concept of poverty is rather vague and cannot be defined in a clear way. In this respect, following a fuzzy logic approach, some new poverty measures are proposed. In particular, the fuzzy extension of two existing poverty measures based on the Gini and Bonferroni inequality indices is provided. Some synthetic and real applications are given in order to show how the proposed poverty measures work.     

Simultaneous confidence intervals on partial means of classes in the two-stage stratified sampling

Let’s consider a finite population of P units, each of them assumes a specific amount of the quantitative variable X. Moreover we assume that the range of values of X is subdivided into k classes and the sampling data come out from a two stage stratified sampling. The main purpose of the work is to determine the estimators, as well as their asymptotic distribution, of the partial means of classes, each of them is defined as a non linear function of the other parameters. Particularly, we are interested in determining the linear approximation estimators and, under convergence theorems, the asymptotic distribution. Afterwards we define the estimator of the vector of the partial means of classes and its asymptotic convergence to multivariate normal distribution is determined. These results are useful to develop simultaneous inferential procedures.