Lessons learned about collaborative evaluation using the Capacity for Applying Project Evaluation (CAPE) framework with school and district leaders

Schools, districts, and state-level educational organizations are experiencing a great shift in the way they do the business of education. This shift focuses on accountability, specifically through the expectation of the effective utilization of evaluative-focused efforts to guide and support decisions about educational program implementation. In as much, education leaders need specific guidance and training on how to plan, implement, and use evaluation to critically examine district and school-level initiatives. One specific effort intended to address this need is through the Capacity for Applying Project Evaluation (CAPE) framework. The CAPE framework is composed of three crucial components: a collection of evaluation resources; a professional development model; and a conceptual framework that guides the work to support evaluation planning and implementation in schools and districts. School and district teams serve as active participants in the professional development and ultimately as formative evaluators of their own school or district-level programs by working collaboratively with evaluation experts. The CAPE framework involves the school and district staff in planning and implementing their evaluation. They are the ones deciding what evaluation questions to ask, which instruments to use, what data to collect, and how and to whom results should be reported. Initially this work is done through careful scaffolding by evaluation experts, where supports are slowly pulled away as the educators gain experience and confidence in their knowledge and skills as evaluators. Since CAPE engages all stakeholders in all stages of the evaluation, the philosophical intentions of these efforts to build capacity for formative evaluation strictly aligns with the collaborative evaluation approach.     

Reaching out to Aggressive Children

Correspondence to Jo Carroll, 3 Barrow Close, Marlborough, Wiltshire SN8 2BD. Summary Social workers are increasingly being asked to offer therapeutichelp to young children who are persistently aggressive and defiant.The difficulties of working with such children, who appear toreject all efforts to help them, are recognized, and some guidanceis offered as to the timing of such work. Directive techniquesoften fail, as the children refuse to participate in any jointactivity. The value of non-directive play therapy as an approachto these children is outlined, and the practicalities of thistechnique are considered. Finally, a case study illustratesthe value of a non-directive approach with a particularly challengingchild.     

Computer-based scheduling of technical resources

This paper considers the design of a Scheduling Sub-System which could be attached to an existing computerised data processing system in order to enhance its overall operation. It draws heavily on the experience of the authors in designing a system to assist in the scheduling of video tape machines within BBC Television.     

Approximate Bayesian Inference in Spatial Generalized Linear Mixed Models

Abstract.  In this paper we propose fast approximate methods for computing posterior marginals in spatial generalized linear mixed models. We consider the common geostatistical case with a high dimensional latent spatial variable and observations at known registration sites. The methods of inference are deterministic, using no simulation-based inference. The first proposed approximation is fast to compute and is 'practically sufficient', meaning that results do not show any bias or dispersion effects that might affect decision making. Our second approximation, an improvement of the first version, is 'practically exact', meaning that one would have to run MCMC simulations for very much longer than is typically done to detect any indication of error in the approximate results. For small-count data the approximations are slightly worse, but still very accurate. Our methods are limited to likelihood functions that give unimodal full conditionals for the latent variable. The methods help to expand the future scope of non-Gaussian geostatistical models as illustrated by applications of model choice, outlier detection and sampling design. The approximations take seconds or minutes of CPU time, in sharp contrast to overnight MCMC runs for solving such problems.     

FINANCIAL MARKET VARIABLES DO NOT PREDICT REAL ACTIVITY

The past decade has seen an extensive empirical reassessment of the information content of financial market variables sensitive to monetary policy. Particularly provocative are recent papers suggesting that some interest rates and interest rate spreads contain more information about economic activity than monetary aggregates. This paper reviews important methodological pitfalls in these studies. We then show that none of the commonly employed measures of monetary policy contain incremental information useful in forecasting real economic activity. Two conclusions are possible. Either monetary policy innovations have no significant real effects, or we (collectively) have failed in our efforts to measure monetary policy. ( JEL E52)     

PRICE PREDICTION ERRORS AND REAL ACTIVITY: A REASSESSMENT

Rational expectations, natural-rate macro-models in which aggregate demand disturbances affect the real sector through price prediction errors, while powerful and tractable analytical tools, are often perceived to be of questionable empirical relevance. This paper reexamines the empirical role of price prediction errors in determining the level of real aggregate activity. The approach is distinguished by accounting for aggregate supply-side disturbances and by more careful treatment of natural rates. Contrary to some previous studies, we find considerable empirical support for the hypothesis that demand-driven price level surprises are positively and significantly correlated with aggregate real economic activity.     

Comparison of Conflict of Interest Policies and Reported Practices in Academic Medical Centers in the United States

The authors reviewed the conflict of interest policies of 9 academic medical centers in the United States and interviewed members of the Institutional Review Boards (IRBs) and Conflict of Interest Committees (COICs) at those institutions. They found that many institutions used processes for reporting and managing conflicts of interest that were more decentralized than the processes described in their policies. Also, most institutions had no clear and comprehensive policy to guide investigators regarding disclosure of conflicts of interest to potential research participants. Considerable differences in understanding of conflict of interest policies were observed between IRB and COIC officials.