Parental leave regulations and the persistence of the male breadwinner model: Using fuzzy-set ideal type analysis to assess gender equality in an enlarged Europe

his paper uses fuzzy-set ideal type analysis to assess the conformity of European leave regulations to four theoretical ideal typical divisions of labour: male breadwinner, caregiver parity, universal breadwinner and universal caregiver. In contrast to the majority of previous studies, the focus of this analysis is on the extent to which leave regulations promote gender equality in the family and the transformation of traditional gender roles. The results of this analysis demonstrate that European countries cluster into five models that only partly coincide with countries’ geographical proximity. Second, none of the countries considered constitutes a universal caregiver model, while the male breadwinner ideal continues to provide the normative reference point for parental leave regulations in a large number of European states. Finally, we witness a growing emphasis at the national and EU levels concerning the universal breadwinner ideal, which leaves gender inequality in unpaid work unproblematized.

Factors affecting a woman's decision to leave an abusive relationship : the theory of planned behaviour /

The present study tested the appHcabiUty of Ajzen's (1985) theory of planned behaviour (TPB), an extension of Fishbein and Ajzen's (1975) theory of reasoned action (TRA), for the first time, in the context of abused women's decision to leave their abusive relationships. The TPB, as a means of predicting women's decision to leave their abusive partners' was drawn from Strube's (1988, 1991) proposed decision-making model based on the principle that the decision-making process is a rational, deliberative process, and regardless of outcome, was a result of a logical assessment of the available data. As a means of predicting those behaviours not under volitional control, Ajzen's (1985) TPB incorporated a measure of perceived behavioural control. Data were collected in two phases, ranging from 6 months to 1 year apart. It was hypothesized that, to the extent that an abused woman held positive attitudes, subjective norms conducive to leaving, and perceived control over leaving, she would form an intention to leave and thus, increase the likelihood of actually leaving her partner. Furthermore, it was expected that perceptions of control would predict leaving behaviour over and above attitude and subjective norm. In addition, severity and frequency of abuse were assessed, as were demographic variables. The TPB failed to account significantly for variability in either intentions or leaving behaviour. All of the variance was attributed to those variables associated with the theory of reasoned action, with social influence emerging as the strongest predictor of a woman's intentions. The poor performance of this model is attributed to measurement problems with aspects of attitude and perceived control, as well as a lack of power due to the small sample size. The insufficiency of perceived control to predict behaviour also suggests that, on the surface at least, other factors may be at work in this context. Implications of these results, and recommendations such as, the importance of obtaining representative samples, the inclusion of self-esteem and emotions as predictor variables in this model, a reevaluation of the target behaviovu" as nonvolitional, and longitudinal studies spanning a longer time period for future research within the context of decision-making are discussed.

An exploration of women elementary school teachers' perceptions of how their decision to return to teaching part-time from a maternity leave influences their professional and personal lives /

The purpose of this research was to explore women elementary teachers' perceptions of how their decision to return to teaching part-time from a maternity leave influences their professional and personal lives. The investigation focused on the decisions surrounding a mother's choice to reenter the teaching profession parttime in a field where each mother had previously been employed full-time. A collective case study was undertaken based on an in-depth interview with five mothers who had made the choice to return to the classroom part-time. The data collected in this study were analyzed and interpreted using qualitative methods. The following four major themes emerged from the interviews: decisionmaking process, challenges faced by mothers who teach part-time, the importance of support, and the enhancement of instructional practice from parenthood. Using these four themes, an analysis was conducted to examine the similarities and differences among the experiences of the participants. The mothers' reflections, my analysis, and the related literature were used at the conclusion of this report to compile implications for teaching practice, theory, and further research.

Permit to Leave Canada, Simon E. Hansler - September 14, 1918

A permit to leave Canada requested by Simon E. Hansler September 14, 1918. The request states that he is permitted to leave Canada on or before December 1, 1918. The document includes his date of birth, eye colour, hair colour, height, occupation and a photograph. Also included on the form, four names to refer for identification. The document states that he is planning to visit relatives in the United States for "a few days".

Which drugs cause preventable admissions to hospital? A systematic review

Aim: Previous systematic reviews have found that drug-related morbidity accounts for 4.3% of preventable hospital admissions. None, however, has identified the drugs most commonly responsible for preventable hospital admissions. The aims of this study were to estimate the percentage of preventable drug-related hospital admissions, the most common drug causes of preventable hospital admissions and the most common underlying causes of preventable drug-related admissions. Methods: Bibliographic databases and reference lists from eligible articles and study authors were the sources for data. Seventeen prospective observational studies reporting the proportion of preventable drug-related hospital admissions, causative drugs and/or the underlying causes of hospital admissions were selected. Included studies used multiple reviewers and/or explicit criteria to assess causality and preventability of hospital admissions. Two investigators abstracted data from all included studies using a purpose-made data extraction form. Results: From 13 papers the median percentage of preventable drug-related admissions to hospital was 3.7% (range 1.4-15.4). From nine papers the majority (51%) of preventable drug-related admissions involved either antiplatelets (16%), diuretics (16%), nonsteroidal anti-inflammatory drugs (11%) or anticoagulants (8%). From five studies the median proportion of preventable drug-related admissions associated with prescribing problems was 30.6% (range 11.1-41.8), with adherence problems 33.3% (range 20.9-41.7) and with monitoring problems 22.2% (range 0-31.3). Conclusions: Four groups of drugs account for more than 50% of the drug groups associated with preventable drug-related hospital admissions. Concentrating interventions on these drug groups could reduce appreciably the number of preventable drug-related admissions to hospital from primary care.

Fast kernel classifier construction using orthogonal forward selection to minimise leave-one-out misclassification rate

We propose a simple yet computationally efficient construction algorithm for two-class kernel classifiers. In order to optimise classifier's generalisation capability, an orthogonal forward selection procedure is used to select kernels one by one by minimising the leave-one-out (LOO) misclassification rate directly. It is shown that the computation of the LOO misclassification rate is very efficient owing to orthogonalisation. Examples are used to demonstrate that the proposed algorithm is a viable alternative to construct sparse two-class kernel classifiers in terms of performance and computational efficiency.

A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate

We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class classifiers in terms of performance and computational efficiency.