The influence of only and even on online semantic interpretation

Focus particles such as only and even indicate that the focused element(s) in a sentence should be contrasted with a set of contextually defined alternatives. Only indicates that properties assigned to the focus set are not shared by elements of the alternative set, whereas even indicates that the focus and alternative sets share the properties mentioned in the sentence. Even has the additional function of marking the focused element as being low on a scale of alternatives ranked in terms of likelihood, thereby signaling that what is being described is somewhat surprising. Using eyetracking, we demonstrate that contrast information associated with only and even is rapidly processed online, with effects for even being delayed, as compared with only (Experiment 1). This difference in time course was not driven by the underlying semantics of the sentence without the focus particle (Experiment 2) but was probably due to even’s more complex semantic function.     

MATHEMATICAL EXPLANATION AND INDISPENSABILITY ARGUMENTS

We defend Joseph Melia's thesis that the role of mathematics in scientific theory is to 'index' quantities, and that even if mathematics is indispensable to scientific explanations of concrete phenomena, it does not explain any of those phenomena. This thesis is defended against objections by Mark Colyvan and Alan Baker.     

Eliciting intelligence from sources informed about counter‐interrogation strategies: An experimental study on the Scharff technique

The Scharff technique aims to elicit information by affecting the source's perception of the interviewer's existing knowledge. Although the technique has been found to be effective for gathering new information, countermeasures to the technique have not been examined. In a 2 × 2 between‐subjects experiment, we informed half of the 120 sources about the counter‐interrogation strategy of carefully considering the interviewer's prior knowledge and the tactic of providing information perceived as already known to the interviewer. After this, sources were interviewed with the Scharff technique or the Direct approach, widely used in human intelligence‐gathering situations and consisting of open‐ended and direct questions. We found that “informed sources” did not succeed in revealing information already known to the interviewer, where informed sources and uninformed sources revealed known information to a similar degree (1.62 pieces vs. 1.65 pieces). Sources interviewed with the Direct approach (vs. Scharff technique) revealed a larger amount of information previously known to the interviewer (2.18 pieces vs. 1.08 pieces). When interviewed with the Scharff technique, sources informed about the counter‐interrogation strategy attempted to adopt more counter‐interrogation strategies. The present study replicates earlier research on the Scharff technique as a technique effective in affecting the source's perception of the interviewer's prior knowledge. The results of the current study indicate that both the Scharff technique and the Direct approach might be similarly robust against counter‐interrogation strategies, in terms of gathering new information. Future studies should focus on implementing more comprehensive training in counter‐interrogation strategies for the sources.     

The Processes of Scientific Discovery: The Strategy of Experimentation

Hans Krebs' discovery, in 1932, of the urea cycle was a major event in biochemistry. This article describes a program, KEKADA, which models the heuristics Hans Krebs used in this discovery. KEKADA reacts to surprises, formulates explanations, and carries out experiments in the same manner as the evidence in the form of laboratory notebooks and interviews indicates Hans Krebs did. Furthermore, we answer a number of questions about the nature of the heuristics used by Krebs, in particular: How domain-specific are the heuristics? To what extent are they idiosyncratic to Krebs? To what extent do they represent general strategies of problem-solving search? The relative generality of KEKADA allows us to view the control structure of KEKADA and its domain-independent heuristics as a model of scientific experimentation that should apply over a broad domain.     

A manifesto for the new MCDA era

The following manifesto has been prepared by five prominent workers in the field of MCDA. We are currently preparing a special issue on the issues that they raise (see Call for Papers on p. 128). We invite you to contribute to the debate in that issue, either in the form of a paper or a letter to the Editor.     

Memory and planning processes in solutions to well-structured problems

Although many studies in the problem-solving literature have considered the factors that might determine the strategies that are employed to solve well-structured problems, these have typically focused upon variants of means-end analysis. In general, such models imply that strategies unfold in a temporally forward direction, that problem solvers typically restrict forward-planning activities to just one or two moves ahead of the current problem state, and that one important heuristic is the avoidance of previous moves. Although studies have demonstrated the importance of such anti-looping heuristics, few have systematically explored the possibility that problem solvers may also plan retrospectively in order to try and assess whether a move might take them back to a state that they have previously visited. Those models of problem solving that promote the role of an anti-looping heuristic have assumed that the ability to use such a heuristic is based upon memory for previous states, but other interpretations are possible. In this paper several studies are reported that attempt systematically to explore participants' attempts to recognize previously visited problem solving states. The findings suggest that there is a systematic relationship between the success of this process, the time taken to make this judgement, and distance from the current state. It is also demonstrated that estimations about where future positions are likely to occur are symmetrical to estimations about past positions. It is suggested that this provides evidence that problem solvers engage in retrospective planning processes in order to try and avoid previous moves, and that this strategy may not be based straightforwardly upon their ability to remember previous problem states.