Errorless learning and memory performance in schizophrenia

There is evidence that patients with schizophrenia have impaired explicit memory and intact implicit memory. The present study sought to replicate and extend that of O'Carroll et al. [O'Carroll, R.E., Russell, H.H., Lawrie, S.M. and Johnstone, E.C., 1999. Errorless learning and the cognitive rehabilitation of memory-impaired schizophrenic patients. Psychological Medicine 29, 105-112.] which reported that for memory-impaired patients with schizophrenia performance on a (cued) word recall task is enhanced using errorless learning techniques (in which errors are prevented during learning) compared to errorful learning (the traditional trial-and-error approach). Thirty patients with a DSM-IV diagnosis of schizophrenia and fifteen healthy controls (HC) participated. The Rivermead Behavioural Memory Test was administered and from their scores, the schizophrenic patients were classified as either memory-impaired (MIS), or memory-unimpaired (MUS). During the training phase two lists of words were learned separately, one using the errorless learning approach and the other using an errorful approach. Subjects were then tested for their recall of the words using cued recall. After errorful learning training, performance on word recall for the MIS group was impaired compared to the MUS and HC groups. However, after errorless learning training, no significant differences in performance were found between the three groups. Errorless learning may play an important role in remediation of cognitive deficits for patients with schizophrenia. (c) 2007 Elsevier Ireland Ltd. All rights reserved.

Uncertainty, learning and growth

The paper extends Blackburn and Galindev's (Economics Letters, Vol. 79 (2003), pp. 417-421) stochastic growth model in which productivity growth entails both external and internal learning behaviour with a constant relative risk aversion utility function and productivity shocks. Consequently, the relationship between long-term growth and short-term volatility depends not only on the relative importance of each learning mechanism but also on a parameter measuring individuals' attitude towards risk.

Learning design contingent valuation (LDCV): NOAA guidelines, preference learning and coherent arbitrariness

We extend the contingent valuation (CV) method to test three differing conceptions of individuals' preferences as either (i) a-priori well-formed or readily divined and revealed through a single dichotomous choice question (as per the NOAA CV guidelines [K. Arrow, R. Solow, P.R. Portney, E.E. Learner, R. Radner, H. Schuman, Report of the NOAA panel on contingent valuation, Fed. Reg. 58 (1993) 4601-4614]); (ii) learned or 'discovered' through a process of repetition and experience [J.A. List, Does market experience eliminate market anomalies? Q. J. Econ. (2003) 41-72; C.R. Plott, Rational individual behaviour in markets and social choice processes: the discovered preference hypothesis, in: K. Arrow, E. Colombatto, M. Perleman, C. Schmidt (Eds.), Rational Foundations of Economic Behaviour, Macmillan, London, St. Martin's, New York, 1996, pp. 225-250]; (iii) internally coherent but strongly influenced by some initial arbitrary anchor [D. Ariely, G. Loewenstein, D. Prelec, 'Coherent arbitrariness': stable demand curves without stable preferences, Q. J. Econ. 118(l) (2003) 73-105]. Findings reject both the first and last of these conceptions in favour of a model in which preferences converge towards standard expectations through a process of repetition and learning. In doing so, we show that such a 'learning design CV method overturns the 'stylised facts' of bias and anchoring within the double bound dichotomous choice elicitation format. (C) 2007 Elsevier Inc. All rights reserved.

Research intensity and knowledge transfer activity in UK universities

As the innovation process has become more open and networked, Government policy in the UK has sought to promote both research excellence in the university sector and the translation of this into economic benefit through university–business engagement. However, this policy approach has tended to be applied uniformly with little account for organisational differences within the sector. In this paper we consider if differences between universities in their research performance is reflected in their knowledge transfer activity. Specifically, as universities develop a commercialization agenda are the strategic priorities for knowledge transfer, the organisational supports in place to facilitate knowledge transfer and the scale and scope of knowledge transfer activity different for high research intensive (HRI) and low research intensive (LRI) universities? The findings demonstrate that universities’ approach to knowledge transfer is shaped by institutional and organisational resources, in particular their ethos and research quality, rather than the capability to undertake knowledge transfer through a Technology Transfer Office (TTO). Strategic priorities for knowledge transfer are reflected in activity, in terms of the dominance of specific knowledge transfer channels, the partners with which universities engage and the geography of business engagement.

The Role of Subjectivity and Knowledge Power Struggles in the Formation of Public Policy

There is a growing incentive for sociologists to demonstrate the use value of their research. Research ‘impact’ is a driver of research funding and a measure of academic standing. Academic debate on this issue has intensified since Burawoy’s (2004) call for a ‘public’ sociology. However the academy is no longer the sole or primary producer of knowledge and empirical sociologists need to contend with the ‘huge swathes’ of social data that now exist (Savage and Burrows, 2007). This article furthers these debates by considering power struggles between competing forms of knowledge. Using a case study, it specifically considers the power struggle between normative and empirical knowledge, and how providers of knowledge assert legitimacy for their truth claims. The article concludes that the idea of ‘impact’ and ‘use-value’ are extremely complex and depends in the policy context on knowledge power struggles, and on how policy makers want to view the world. © The Author(s) 2012