The suppression of q card selections: Evidence for deductive inference in Wason's Selection Task

The results of three experiments investigating the role of deductive inference in Wason's selection task are reported. In Experiment 1, participants received either a standard one-rule problem or a task containing a second rule, which specified an alternative antecedent. Both groups of participants were asked to select those cards that they considered were necessary to test whether the rule common to both problems was true or false. The results showed a significant suppression of q card selections in the two-rule condition. In addition there was weak evidence for both decreased p selection and increased not-q selection. In Experiment 2 we again manipulated number of rules and found suppression of q card selections only. Finally, in Experiment 3 we compared one- and two-rule conditions with a two-rule condition where the second rule specified two alternative antecedents in the form of a disjunction. The q card selections were suppressed in both of the two-rule conditions but there was no effect of whether the second rule contained one or two alternative antecedents. We argue that our results support the claim that people make inferences about the unseen side of the cards when engaging with the indicative selection task.

Deciding between accounts of the selection task: A reply to Oaksford (2002)

In this paper we report on our attempts to fit the optimal data selection (ODS) model (Oaksford Chater, 1994; Oaksford, Chater, & Larkin, 2000) to the selection task data reported in Feeney and Handley (2000) and Handley, Feeney, and Harper (2002). Although Oaksford (2002b) reports good fits to the data described in Feeney and Handley (2000), the model does not adequately capture the data described in Handley et al. (2002). Furthermore, across all six of the experiments modelled here, the ODS model does not predict participants' behaviour at the level of selection rates for individual cards. Finally, when people's probability estimates are used in the modelling exercise, the model adequately captures only I out of 18 conditions described in Handley et al. We discuss the implications of these results for models of the selection task and claim that they support deductive, rather than probabilistic, accounts of the task.

Brunetta’s reform swan song? An assessment of its success in local governments through the analysis of its tools

The work aims at assessing the success of Brunetta’s reform (Legislative Decree n. 150/2009), a far-reaching reform that aimed at improving both organizational and individual performance in Italian public administration through a specific planning and control process (the performance cycle) and most of all through two new tools, Performance Plan and Performance Report. The success of the reform is assessed, with particular emphasis on local governments, analyzing the diffusion and use of these new tools. The study has been conducted using a deductive-inductive methodology. Thus, after a study of managerial reforms in Italy and performance measurement literature, a possible model (PerformEL Model) local governments could follow to draw up Performance Plan and Report as effective tools for performance measurement has been designed (deductive phase). Performance Plans 2011-2013 and Performance Report 2011 downloaded from Italian big sized municipalities’ websites have been analyzed in the light of PerformEL Model, to assess the diffusion of the documents and their coherence with legal requirements and suggestions from literature (inductive phase). Data arising from the empirical analysis have been studied to evaluate the diffusion and the effectiveness of big sized municipalities’ Performance Plans and Reports as performance measurement tools and thus to assess the success of the reform (feedback phase). The study shows a scarce diffusion of the documents; they are mostly drew up because of their compulsoriness or to gain legitimization. The results testify the failure of Brunetta’s reform, at least with regard to local governments.