Suchergebnisse

The data set 'Estonian national candidate data 1992-2015' provides information on the candidates for Estonian parliament between 1992 and 2015. The data set covers seven national elections and includes such information as the candidate name, gender, age, education, party membership and also information on the election results, such as votes for candidates, parties and total votes cast in districts. A full list of variables is provided below. The raw data comes from the Estonian National Electoral Committee (www.vvk.ee) and I would like to acknowledge their help in compiling these data. This data file provides the information on candidates and election results in a single document. In addition, many variables, such as incumbency, gender, vote shares, etc. have been added to the original data made public by the electoral committee.

The literature on women's descriptive representation has looked at the debate on open and closed lists as a choice between electoral systems. This article instead focuses on whether voters or the parties are biased against female candidates. Using data from six Estonian elections, the article finds that voters are not consistently biased against female candidates and open lists do not necessarily decrease women's representation. However, unknown and non-incumbent female candidates fare significantly worse than similar men. The analysis also shows that parties do not place women in electable positions on closed lists, and closed lists do not improve women's representation.

This dissertation studies the descriptive (i.e. numeric) representation of women in national parliaments in three related but independent papers. The empirical analysis presented in the papers is based on two original data sets. The first, macro level data set covers the democratic elections of 75 nations between the years 1980 and 2010. A subset of these data covering the OECD nations is augmented to include a set of socioeconomic variables that were not available for other countries. The second data set is a collection of candidate data from six Estonian elections between the years 1992 and 2011. The papers use a variety of quantitative techniques to support the theoretical claims made in them. ; TARA (Trinity?s Access to Research Archive) has a robust takedown policy. Please contact us if you have any concerns: rssadmin@tcd.ie

We find that strategic sequencing & other factors sort parties roughly into two groups. Low-ranking parties lose part of their inherent support, compared to probabilistic expectations, while high-ranking parties profit from the shift. Our method is to graph the worldwide mean seat shares of parties at various ranks by size against the largest party share (Nagayama triangle format). The resulting empirical pattern looks complex, yet when we adjust a probabilistic model to account for strategic & other factors that may hurt the smaller parties, the fit becomes close. The number of parties that profit from transfers is close to the inverse of the fractional share of the largest party. The model fits best when the transfer is assumed to involve about one-half of inherent minor party support. This is a novel way to estimate the universal average strength of strategic & other factors that work against the smaller parties. The empirical worldwide mean pattern offers us a norm against which seat share distributions in individual countries or single elections can be compared. Tables, Figures, Appendixes, References. [Copyright 2006 Elsevier Ltd.]

ObjectivesCare experienced people have poorer health in UK and internationally, but the direction of causation is debated. Using longitudinal cross-sectoral data linkage we explore if inequalities in diabetes prevalence and hospitalisation are present before entering care or develop during or after leaving care.
ApproachHealth and social care data were linked for 13,830 care experienced children (CEC) and together with 649,771 general population children (GPC) their prescriptions and hospitalisations were followed from birth between 1990-2004 to study end in 2016. Diabetes prevalence was estimated as at least one prescription or inpatient hospitalisation for diabetes. We compared hospitalisation percentages and rates in the two cohorts by age and gender. Results from multivariable models adjusted for socioeconomic status, age, gender, care type/length, local authority, and comorbidities will be presented at conference.
ResultsDiabetes prevalence was similar in both cohorts and higher in females. However, CEC had twice as many hospitalisations as GPC. Mean hospitalisations were highest among care experienced males (6 compared to 3.6 in females and 2 in GPC). 24% of CEC were hospitalised 3-9 times and 13% 10+ times, for GPC these were 19% and 3% respectively. Hospitalisation rates increase with age in both cohorts, as do differences between cohorts. At ages 0-4 hospitalisation rates are similar, by ages 12-15 CEC have twice as high and at ages 18-27 4-times higher hospitalisation rates. Among CEC, across all ages hospitalisation rates are lower while the child is in care, with the lowest rates in foster care. Hospitalisation rates are highest before entering and after leaving care.
ConclusionResults for diabetes hospitalisations suggest that being in care can be good for children's health. However, a sudden withdrawal of support can create a "cliff edge" and health may deteriorate after leaving care. Data linkage has significant potential to inform policy and practice, including supporting CEC after leaving care.

PURPOSE: The Children's Health in Care in Scotland Cohorts were set up to provide first population-wide evidence on the health outcomes of care experienced children (CEC) compared with children in the general population (CGP). To date, there are no data on how objective health outcomes, mortality and pregnancies for CEC are different from CGP in Scotland. PARTICIPANTS: The CEC cohort includes school-aged children who were on the 2009/2010 Scottish Government's Children Looked After Statistics (CLAS) return and on the 2009 Pupil Census (PC). The children in the general population cohort includes those who were on the 2009 PC and not on any of the CLAS returns between 1 April 2007 and 31 July 2016. FINDINGS TO DATE: Data on a variety of health outcomes, including mortality, prescriptions, hospitalisations, pregnancies, and Accident & Emergency attendances, were obtained for the period 1 August 2009 to 31 July 2016 for both cohorts. Data on socioeconomic status (SES) for both cohorts were available from the Birth Registrations and a small area deprivation measure was available from the PC. CEC have, on average, lower SES at birth and live in areas of higher deprivation compared with CGP. A higher proportion of CEC have recorded events across all health data sets, and they experienced higher average rates of mortality, prescriptions and hospitalisations during the study period. The reasons for contacting health services vary between cohorts. FUTURE PLANS: Age-standardised rates for the two cohorts by sex and area deprivation will be calculated to provide evidence on population-wide prevalence of main causes of death, reasons for hospitalisation and types of prescription. Event history analysis will be used on matched cohorts to investigate the impact of placement histories and socioeconomic factors on health.

Purpose: The Children's Health in Care in Scotland Cohorts were set up to provide first population-wide evidence on the health outcomes of care experienced children (CEC) compared with children in the general population (CGP). To date, there are no data on how objective health outcomes, mortality and pregnancies for CEC are different from CGP in Scotland. Participants: The CEC cohort includes school-aged children who were on the 2009/2010 Scottish Government's Children Looked After Statistics (CLAS) return and on the 2009 Pupil Census (PC). The children in the general population cohort includes those who were on the 2009 PC and not on any of the CLAS returns between 1 April 2007 and 31 July 2016. Findings to date: Data on a variety of health outcomes, including mortality, prescriptions, hospitalisations, pregnancies, and Accident & Emergency attendances, were obtained for the period 1 August 2009 to 31 July 2016 for both cohorts. Data on socioeconomic status (SES) for both cohorts were available from the Birth Registrations and a small area deprivation measure was available from the PC. CEC have, on average, lower SES at birth and live in areas of higher deprivation compared with CGP. A higher proportion of CEC have recorded events across all health data sets, and they experienced higher average rates of mortality, prescriptions and hospitalisations during the study period. The reasons for contacting health services vary between cohorts. Future plans: Age-standardised rates for the two cohorts by sex and area deprivation will be calculated to provide evidence on population-wide prevalence of main causes of death, reasons for hospitalisation and types of prescription. Event history analysis will be used on matched cohorts to investigate the impact of placement histories and socioeconomic factors on health.

Purpose: The Children's Health in Care in Scotland Cohorts were set up to provide first population-wide evidence on the health outcomes of care experienced children (CEC) compared with children in the general population (CGP). To date, there are no data on how objective health outcomes, mortality and pregnancies for CEC are different from CGP in Scotland. Participants: The CEC cohort includes school-aged children who were on the 2009/2010 Scottish Government's Children Looked After Statistics (CLAS) return and on the 2009 Pupil Census (PC). The children in the general population cohort includes those who were on the 2009 PC and not on any of the CLAS returns between 1 April 2007 and 31 July 2016. Findings to date: Data on a variety of health outcomes, including mortality, prescriptions, hospitalisations, pregnancies, and Accident & Emergency attendances, were obtained for the period 1 August 2009 to 31 July 2016 for both cohorts. Data on socioeconomic status (SES) for both cohorts were available from the Birth Registrations and a small area deprivation measure was available from the PC. CEC have, on average, lower SES at birth and live in areas of higher deprivation compared with CGP. A higher proportion of CEC have recorded events across all health data sets, and they experienced higher average rates of mortality, prescriptions and hospitalisations during the study period. The reasons for contacting health services vary between cohorts. Future plans: Age-standardised rates for the two cohorts by sex and area deprivation will be calculated to provide evidence on population-wide prevalence of main causes of death, reasons for hospitalisation and types of prescription. Event history analysis will be used on matched cohorts to investigate the impact of placement histories and socioeconomic factors on health.

ObjectivesWe sought to describe barriers and facilitators faced by three research projects aiming to link routinely-collected data across various sectors, to produce evidence to inform healthy public policy. We conducted these case studies as a part of a wider research project on cross-sectoral sharing and linkage of secondary data.
ApproachWe selected the case studies to cover a range of target populations and datasets. The chosen projects investigated (1) the health of care-experienced children; (2) the intersection of homelessness, justice involvement, drug use, and severe mental illness; (3) multi-morbidity among adults receiving social care. Information about timelines and governance processes was collected from lead investigators, including specific barriers and facilitators encountered, using a standardised pro forma and follow-up interviews. Thematic analysis was carried out by the research team, informed by themes identified in a parallel scoping review of existing literature on evidence use for healthy public policy and practice.
ResultsEach project involved between 6 and 11 agencies, with co-ordination across multiple institutions and geographies proving challenging. Due to challenges encountered, all projects had to amend their original geographical or demographic scope. Forty-four barriers and facilitators to sharing and linkage of cross-sectoral routinely-collected data for public health research were identified. These included but were not limited to: integration of current data in an ever-changing linkage landscape; the need for timely feedback in undertaking the study; standardisation of information governance processes; highlighting the resourcing and funding issues for data linkage projects; the need for data controllers to recognise the value of such projects; and issues relating to staff turnover and workload pressures.
ConclusionThe interconnected nature of barriers and facilitators identified by the case studies suggests the importance of a whole-systems approach to cross-sectoral linkage. While literature offers relatively few case studies of cross-sectoral linkage for health research, the value of their insight into the linkage landscape derived from real-life experience is substantial.

OBJECTIVE: To describe and assess currently used area-based measures of deprivation in Brazil for health research, to the purpose of informing the development of a future small area deprivation index. METHODS: We searched five electronic databases and seven websites of Brazilian research institutions and governmental agencies. Inclusion criteria were: studies proposing measures of deprivation for small areas (i.e., finer geography than country-level) in Brazil, published in English, Portuguese or Spanish. After data-extraction, results were tabulated according to the area level the deprivation measure was created for and to the dimensions of deprivation or poverty included in the measures. A narrative synthesis approach was used to summarize the measures available, highlighting their utility for public health research. RESULTS: A total of 7,199 records were retrieved, 126 full-text articles were assessed after inclusion criteria and a final list of 30 articles was selected. No small-area deprivation measures that have been applied to the whole of Brazil were found. Existing measures were mainly used to study infectious and parasitic diseases. Few studies used the measures to assess inequalities in mortality and no studies used the deprivation measure to evaluate the impact of social programs. CONCLUSIONS: No up-to-date small area-based deprivation measure in Brazil covers the whole country. There is a need to develop such an index for Brazil to measure and monitor inequalities in health and mortality, particularly to assess progress in Brazil against the Sustainable Development Goal targets for different health outcomes, showing progress by socioeconomic groups.