Demographic Shifts in the Czech Republic after 1989: A Second Demographic Transition View

A dramatic change in fertility,family formation and living arrangements tookplace in the Czech Republic over the 1990s. Theestablishment of democracy, profound socialtransformation and transition to the marketeconomy affected the values and demographicbehaviour of the young Czech generation. Thispaper examines whether these demographic shiftscan be interpreted within the framework of thesecond demographic transition. The theoreticalpart discusses the idea of the transition,outlining three distinctive conceptualisations.Two of them – the view of the transition as aprogression of characteristic interrelateddemographic changes and a broader viewstressing the importance of underlyingideational factors – fit the Czech situationvery well. A comparison with the Netherlandsreveals that the onset of the transition in theCzech Republic may be clearly located in thefirst half of the 1990s, lagging two decadesbehind the Netherlands.     

Population growth and economic development

The paper deals with the relationship between the population growth and economic development in Yugoslavia and its republics, covering the period after the Second World War. Yugoslavia is a developing country with a specific demographic and economic structure which makes her unique in Europe. Its territory is comprised of both relatively developed regions where demographic transition is over, and underdeveloped regions with high natural increase of population where the demographic transition is only just beginning. Correlation and regression methods were used to quantify this relationship. The economic development and structural changes are discussed, relating to human factor. An adequate population policy through family planning is stressed as important in obtaining an increased return to scale with a more positive role of demographic factor.     

Industry and the environment: a case study of cleaner technologies in selected European countries

The aim of this case study is to discuss the role of technology in addressing environmental problems. The paper tries to scratch beneath the surface of the increasingly frequent ‘quick-fix’ solutions to the present environmental problems, based on such beguiling catchwords as Cleaner Technologies, Best Available Technologies, and Best Available Technologies Not Exceeding Excessive Costs, etc., in an attempt to discover whether there is any substance in them, or whether they are just full of hot air. Recent data from case studies performed by the author in Germany and Finland as well as a postal questionnaire in Denmark are presented. The paper analyses and discusses the roles and responsibilities of designers, industrialists, and government policy-makers. It is argued that existing regulatory regimes, supranational industrial structures, and market mechanisms do not favour the development of cleaner technologies, nor do they promote a reduction in consumption patterns. Evidence from ongoing empirical research in Northwest Europe suggests that industry is far from developing and/or implementing cleaner technologies. The paper closes with a discussion of some of the policy implications involved and some examples of urgently needed further research.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.     

Job-Related Well-Being of Immigrants

Social Indicators Research - Considerable literature exists on the acculturation and adaptation of immigrants. For the most part, studies looked at their psychological and social adaptation to the...     

Utilization of Mixed Distributions in the Calculation of Polarization: The Case of Spain

Social Indicators Research - This study analyzes the evolution of salary polarization in the Spanish labor market. The paper proposes the use of mixed distributions to examine the consequences of...     

The Use of Telematics Devices to Improve Automobile Insurance Rates

Most automobile insurance databases contain a large number of policyholders with zero claims. This high frequency of zeros may reflect the fact that some insureds make little use of their vehicle, or that they do not wish to make a claim for small accidents in order to avoid an increase in their premium, but it might also be because of good driving. We analyze information on exposure to risk and driving habits using telematics data from a pay‐as‐you‐drive sample of insureds. We include distance traveled per year as part of an offset in a zero‐inflated Poisson model to predict the excess of zeros. We show the existence of a learning effect for large values of distance traveled, so that longer driving should result in higher premiums, but there should be a discount for drivers who accumulate longer distances over time due to the increased proportion of zero claims. We confirm that speed limit violations and driving in urban areas increase the expected number of accident claims. We discuss how telematics information can be used to design better insurance and to improve traffic safety.