The role of pecuniary and non-pecuniary factors in teacher turnover and mobility decisions

We investigate the determinants of teacher exits from and mobility within the Queensland state school system. In common with previous research we find that non-pecuniary factors, such as class size and location, affect movement decisions but our results suggest a significant role for pecuniary factors. In particular, higher wages reduce exits from the public sector, especially in the case of more experienced female teachers. Locality allowances paid to teachers in rural and remote schools, where non-pecuniary factors are less attractive, appear to have some success in attracting and retaining staff in these locations

Funding, school specialisation and test scores

We evaluate the effect on test scores of a UK education reform which has increased <br/>funding of schools and encouraged their specialisation in particular subject areas, enhancing pupil choice and competition between schools. Using several data sets, we apply cross-sectional and difference-in-differences matching models, to confront issues of the choice of an appropriate control group and different forms of selection bias. We demonstrate a statistically significant causal effect of the specialist schools policy on test score outcomes. The duration of specialisation matters, and we consistently find that the longer a school has been specialist the larger is the impact on test scores. We finally disentangle the funding effect from a specialisation effect, and the latter occurs yielding relatively large improvements in test scores in particular subjects.

Scientific publications and presentations relating to planetary quarantine. Volume 5 - The 1969 supplement

Bibliography on planetary quarantin

Worker absence and shirking: evidence from matched teacher-school data

We utilise a unique matched teacher-school data set of absenteeism records to quantify shirking behaviour in primary and secondary schools. Shirking behaviour is shown to vary systematically across schools, and hence schools are characterised as either healthy (low absenteeism) or sick (high absenteeism). Using count data techniques, and allowing for the problems of unobserved heterogeneity and partial observability in our data, we find that teachers in sick schools have higher absence rates. Our estimates suggest that shirking behaviour can account for 24 percent to 38 percent of recorded absenteeism. Furthermore, a teacher who moves from a healthy school to a sick school is likely to face an increased risk of absenteeism of up to 70 percent. As the factors a¤ecting involuntary absenteeism are unlikely to change in the short run, we argue that this increased incidence in absenteeism re?ects the impact of the change in school environment on shirking behaviour.

The role of pecuniary and non-pecuniary factors in teacher turnover and mobility decisions

We investigate the determinants of teacher exits from and mobility within the Queensland state school system. In common with previous research we find that non-pecuniary factors, such as class size and location, affect movement decisions but our results suggest a significant role for pecuniary factors. In particular, higher wages reduce exits from the public sector, especially in the case of more experienced female teachers. Locality allowances paid to teachers in rural and remote schools, where non-pecuniary factors are less attractive, appear to have some success in attracting and retaining staff in these locations.

Onset of the Immune Response

In our studies on the primary immune response, we have used germfree, colostrum-deprived swine taken three to five days prematurely by hysterectomy. These piglets lack gamma globulin until they are immunized. Upon antigenic stimulation, early macroglobulin antibody is produced within 48 hours; subsequently late euglobulin antibody is produced. Our results have led me to formulate a new instructive model for the onset of antibody formation

A New Method to Improve the Sensitivity of Leak Detection in Self-Contained Fluid-filled Cables

A method of real-time detection of leaks for self-contained fluid-filled cables without taking them out of service has been assessed and a novel machine learning technique, i.e. support vector regression (SVR) analysis has been investigated to improve the detection sensitivity of the self-contained fluid-filled (FF) cable leaks. The condition of a 400 kV underground FF cable route within the National Grid transmission network has been monitored by Drallim pressure, temperature and load current measurement system. These three measured variables are used as parameters to describe the condition of the cable system. In the regression analysis the temperature and load current of the cable circuit are used as independent variables and the pressure within cables is the dependent variable to be predicted. As a supervised learning algorithm, the SVR requires data with known attributes as training samples in the learning process and can be used to identify unknown data or predict future trends. The load current is an independent variable to the fluid-filled system itself. The temperature, namely the tank temperature is determined by both the load current and the weather condition i.e. ambient temperature. The pressure is directly relevant to the temperature and therefore also correlated to the load current. The Gaussian-RBF kernel has been used in this investigation as it has a good performance in general application. The SVR algorithm was trained using 4 days data, as shown in Figure 1, and the optimized SVR is used to predict the pressure using the given load current and temperature information