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from the article: Abstract Based on a review of recent literature, this paper addresses the question of how urban planners can steer urban environmental quality, given the fact that it is multidimensional in character, is assessed largely in subjective terms and varies across time. The paper explores three questions that are at the core of planning and designing cities: ‘quality of what?’, ‘quality for whom?’ and ‘quality at what time?’ and illustrates the dilemmas that urban planners face in answering these questions. The three questions provide a novel framework that offers urban planners perspectives for action in finding their way out of the dilemmas identified. Rather than further detailing the exact nature of urban quality, these perspectives call for an approach to urban planning that is integrated, participative and adaptive. ; ; sustainable urban development; trade-offs; quality dimensions
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Frequent claims are made for the importance of the hospitality industry, and wider tourism sector, as potential and actual creators of employment. Many of these claims emanate from industry representative and advocacy organizations, often as part of their legitimate efforts to lobby governments for favourable treatment of their sectors. Good quality universal statistical data on employment in hospitality are noticeable by their absence, although information collected by bodies such as the International Labour Organization is extensive. This paper reviews the current state of data availability on global hospitality employment (with a primary focus on commercial hospitality operations) and seeks to employ these secondary sources in investigating the question as to whether we can in fact make plausible statements about the extent of such employment. This exercise is important both to contextualizing claims made for the employment generating capacity of the hospitality industry and to shedding light on the degree of seriousness with which data might be treated in wider policy contexts. The paper concludes, with cautious optimism, that commercial hospitality is a significant global employer and that the claims made for this employment by representative and advocacy organizations are plausible if treated with circumspection.
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Challenges that surveys are facing are increasing data collection costs and declining budgets. During the past years, many surveys at Statistics Netherlands were redesigned to reduce costs and to increase or maintain response rates. From 2018 onwards, adaptive survey design has been applied in several social surveys to produce more accurate statistics within the same budget. In previous years, research has been done into the effect on quality and costs of reducing the use of interviewers in mixed-mode surveys starting with internet observation, followed by telephone or face-to-face observation of internet nonrespondents. Reducing follow-ups can be done in different ways. By using stratified selection of people eligible for follow-up, nonresponse bias may be reduced. The main decisions to be made are how to divide the population into strata and how to compute the allocation probabilities for face-to-face and telephone observation in the different strata. Currently, adaptive survey design is an option in redesigns of social surveys at Statistics Netherlands. In 2018 it has been implemented in the Health Survey and the Public Opinion Survey, in 2019 in the Life Style Monitor and the Leisure Omnibus, in 2021 in the Labour Force Survey, and in 2022 it is planned for the Social Coherence Survey. This paper elaborates on the development of the adaptive survey design for the Labour Force Survey. Attention is paid to the survey design, in particular the sampling design, the data collection constraints, the choice of the strata for the adaptive design, the calculation of follow-up fractions by mode of observation and stratum, the practical implementation of the adaptive design, and the six-month parallel design with corresponding response results.
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The aim of this QSR 2022 on tourism is to make an attempt to assess available information about the tourism industry from three countries and various sources and present it in a comprehensive manner. We, thereby, describe common features of regional tourism structures, as well as differences, and we present some of the identified data incompatibilities (sections 2.2 and 2.3). The recommendations in section 3 present avenues along which data collection and monitoring can be improved, inspired by a set of key forces driving change intourism that stakeholders should be prepared for (section 2.4).
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Among other things, learning to write entails learning how to use complex sentences effectively in discourse. Some research has therefore focused on relating measures of syntactic complexity to text quality. Apart from the fact that the existing research on this topic appears inconclusive, most of it has been conducted in English L1 contexts. This is potentially problematic, since relevant syntactic indices may not be the same across languages. The current study is the first to explore which syntactic features predict text quality in Dutch secondary school students’ argumentative writing. In order to do so, the quality of 125 argumentative essays written by students was rated and the syntactic features of the texts were analyzed. A multilevel regression analysis was then used to investigate which features contribute to text quality. The resulting model (explaining 14.5% of the variance in text quality) shows that the relative number of finite clauses and the ratio between the number of relative clauses and the number of finite clauses positively predict text quality. Discrepancies between our findings and those of previous studies indicate that the relations between syntactic features and text quality may vary based on factors such as language and genre. Additional (cross-linguistic) research is needed to gain a more complete understanding of the relationships between syntactic constructions and text quality and the potential moderating role of language and genre.
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Abstract Purpose To determine the predictive value of quality of life for mortality at the domain and item levels. Methods This longitudinal study was carried out in a sample of 479 Dutch people aged 75 years or older living independently, using a follow-up of 7 years. Participants completed a self-report questionnaire. Quality of life was assessed with the WHOQOL-BREF, including four domains: physical health, psychological, social relationships, and environment. The municipality of Roosendaal (a town in the Netherlands) indicated the dates of death of the individuals. Results Based on mean, all quality of life domains predicted mortality adjusted for gender, age, marital status, education, and income. The hazard ratios ranged from 0.811 (psychological) to 0.933 (social relationships). The areas under the curve (AUCs) of the four domains were 0.730 (physical health), 0.723 (psychological), 0.693 (social relationships), and 0.700 (environment). In all quality of life domains, at least one item predicted mortality (adjusted). Conclusion Our study showed that all four quality of life domains belonging to the WHOQOL-BREF predict mortality in a sample of Dutch community-dwelling older people using a follow-up period of 7 years. Two AUCs were above threshold (psychological, physical health). The findings offer health care and welfare professionals evidence for conducting interventions to reduce the risk of premature death.
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Objective: The aim of this cross-sectional study was to determine the associations between frailty and multimorbidity on the one hand and quality of life on the other in community-dwelling older people. Methods: A questionnaire was sent to all people aged 70 years and older belonging to a general practice in the Netherlands; 241 persons completed the questionnaire (response rate 47.5%). For determining multimorbidity, nine chronic diseases were examined by self-report. Frailty was assessed by the Tilburg Frailty Indicator, and quality of life was assessed by the World Health Organization Quality of Life Instrument—Older Adults Module. Results: Multimorbidity, physical, psychological, as well as social frailty components were negatively associated with quality of life. Multimorbidity and all 15 frailty components together explained 11.6% and 36.5% of the variance of the score on quality of life, respectively. Conclusion: Health care professionals should focus their interventions on the physical, psychological, and social domains of human functioning. Interprofessional cooperation between health care professionals and welfare professionals seems necessary to be able to meet the needs of frail older people.
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