What constitutes globalised evidence? Cultural tensions and critical reflections of the evidence-based movement in New Zealand

The evidence-based movement (EBM) is grounded in a well-intentioned desire to ensure resources are invested in high quality initiatives that generate the intended impact. Nevertheless, recent critiques contest the appropriateness of translating an approach rooted in a medical model to socially complex initiatives. Globalised notions of evidence can also be damaging for programs operating in small, culturally diverse countries with limited resources. Given these polemic views, our aim was to examine local perceptions of the EBM in New Zealand, a small, vibrant, bicultural society with a mix of homegrown and imported programs. Using a snowball sampling approach, 79 professionals working in the education and social sectors completed an anonymous online survey that contained a series of closed and open-ended questions. The results show that although participants positively endorsed a variety of quality evidence markers, traditionally positivist methodological leanings received lower and more varied endorsements compared to more inclusive and pluralistic approaches. Many also expressed concern that the EBM emphasises a narrow and colonised view of evidence that does not align with Māori and Pacific worldviews, and undermines innovation. We discuss the implications as an avenue for advancing intervention and social programming research in an increasingly multicultural and globalised world.     

An automated test development of parallel tests from a seed test

Binary programming models are presented to generate parallel tests from an itembank. The parallel tests are created to match item for item an existing seed test and match user supplied taxonomic specifications. The taxonomic specifications may be either obtained from the seed test or from some other user requirement. An algorithm is presented along with computational results to indicate the overall efficiency of the process. Empirical findings based on an itembank for the Arithmetic Reasoning section of the Armed Services Vocational Aptitude Battery are given.The Office of Naval Research, Program in Cognitive Science, N00014-87-C-0696 partially supported the work of Douglas H. Jones. The Rutgers Research Resource Committee of the Graduate School of Management partially supported the work of Douglas H. Jones and Ing-Long Wu. A Thomas and Betts research fellowship partially supported the work of Ing-Long Wu. The Human Resources Laboratory, United States Air Force, partially supported the work of Ronald Armstrong. The authors benefited from conversations with Dr. Wayne Shore, Operational Technologies, San Antonio, Texas. The order of authors' names is alphabetical and denotes equal authorship.     

TRAINING PRESCHOOL CHILDREN TO RECRUIT NATURAL COMMUNITIES OF REINFORCEMENT1

Four normal and four deviant children aged four-to-six years were taught to judge the quality of their academic work in a preschool classroom, and to prompt or cue their teachers to comment about the quality of that work. When these skills did not generalize spontaneously to other teachers in concurrent natural situations, generalized responding was taught by the experimenter, in multiple-baseline design across subjects. This generalization programming enabled the children to contact a sometimes dormant, but readily available natural community of teacher praise and reinforcement, i.e., to recruit an increase in cued praise and schedules of praise for their good work. These behaviors may be important to young children who find themselves bereft of attention in classrooms.     

TEACHING PEDESTRIAN SKILLS TO RETARDED PERSONS: GENERALIZATION FROM THE CLASSROOM TO THE NATURAL ENVIRONMENT1

Little attention has been given to teaching adaptive community skills to retarded persons. In this study, five retarded male students were taught basic pedestrian skills in a classroom. Training was conducted on a model built to simulate city traffic conditions. Each subject was taught five specific skills involved in street crossing in sequence, viz. intersection recognition, pedestrian-light skills, traffic-light skills, and skills for two different stop-sign conditions. Before, during, and after training, subjects were tested on generalization probes on the model and under actual city traffic conditions. Results of a multiple-baseline design across both subjects and behaviors indicated that after receiving classroom training on the skills, each subject exhibited appropriate pedestrian skills under city traffic conditions. In addition, training in some skills appeared to facilitate performance in skills not yet trained.     

Fitting and testing carroll's weighted unfolding model for preferences

A quadratic programming algorithm is presented for fitting Carroll's weighted unfolding model for preferences to known multidimensional scale values. The algorithm can be applied directly to pairwise preferences; it permits nonnegativity constraints on subject weights; and it provides a means of testing various preference model hypotheses. While basically metric, it can be combined with Kruskal's monotone regression to fit ordinal data. Monte Carlo results show that (a) adequacy of true preference recovery depends on the number of data points and the amount of error, and (b) the proportion of data variance accounted for by the model sometimes only approximately reflects true recovery.This study is based on a doctoral dissertation submitted to the University of Illinois at Urbana-Champaign. The author wishes to thank the members of his dissertation committee—Lawrence E. Jones, Chairman, Charles Lewis, Stephen Golding, Ledyard Tucker, and Nancy Wiggins—for their helpful comments.     

The Role of Emotional Content and Perceptual Saliency During the Programming of Saccades Toward Faces

Previous studies have shown that the human visual system can detect a face and elicit a saccadic eye movement toward it very efficiently compared to other categories of visual stimuli. In the first experiment, we tested the influence of facial expressions on fast face detection using a saccadic choice task. Face-vehicle pairs were simultaneously presented and participants were asked to saccade toward the target (the face or the vehicle). We observed that saccades toward faces were initiated faster, and more often in the correct direction, than saccades toward vehicles, regardless of the facial expressions (happy, fearful, or neutral). We also observed that saccade endpoints on face images were lower when the face was happy and higher when it was neutral. In the second experiment, we explicitly tested the detection of facial expressions. We used a saccadic choice task with emotional-neutral pairs of faces and participants were asked to saccade toward the emotional (happy or fearful) or the neutral face. Participants were faster when they were asked to saccade toward the emotional face. They also made fewer errors, especially when the emotional face was happy. Using computational modeling, we showed that this happy face advantage can, at least partly, be explained by perceptual factors. Also, saccade endpoints were lower when the target was happy than when it was fearful. Overall, we suggest that there is no automatic prioritization of emotional faces, at least for saccades with short latencies, but that salient local face features can automatically attract attention.     

Cognitive computing models for estimation of reference evapotranspiration: A review

Irrigation practices can be advanced by the aid of cognitive computing models. Repeated droughts, population expansion and the impact of global warming collectively impose rigorous restrictions over irrigation practices. Reference evapotranspiration (ET₀) is a vital factor to predict the crop water requirements based on climate data. There are many techniques available for the prediction of ET₀. An efficient ET₀ prediction model plays an important role in irrigation system to increase water productivity. In the present study, a review has been carried out over cognitive computing models used for the estimation of ET₀. Review exhibits that artificial neural network (ANN) approach outperforms support vector machine (SVM) and genetic programming (GP). Second order neural network (SONN) is the most promising approach among ANN models.     

Generating interior search directions for multiobjective linear programming

A new multiobjective linear programming (MOLP) algorithm is presented. The algorithm uses a variant of Karmarkar's interior-point algorithm known as the affine-scaling primal algorithm. Using this single-objective algorithm, interior search directions are generated and used to provide an approximation to the gradient of the (implicitly known) utility function. The approximation is guided by assessing locally relevant preference information for the various interior directions through interaction with a decision maker (DM). The resulting algorithm is an interactive approach that makes its progress towards the solution through the interior of the constraints polytope.     

Economic optimization by compromise programming: The joint production model

In a basic microeconomic model (joint production and consumer's utility curves) three key optima appear: the best technological mix, the maximum profit point and the consumer's utility optimum. Compromise analysis can help to clarify their connections. This paper and other recent research attempt to specify the conditions which guarantee that these three optima coincide. Thus compromise programming becomes a valuable surrogate of economic optimization.     

Resolution of dilemmas: A mathematical theory

A mathematical formulation for a dilemma (i.e. a situation in which a very difficult choice between two alternatives must be made) is given. Multiple-objective programming is assumed as the model for a single decision maker. It is shown that, in principle, any dilemma is resolvable. Furthermore, there is always more than one way in which to resolve a dilemma. Illustrative examples from non-convex optimization are presented.