CRIME RELAPSE AND ITS PREVENTION

2017 ◽  
Vol 1 (78) ◽  
pp. 22
Author(s):  
Ilga Trubiņa
Keyword(s):  
Data Collection ◽  
Statistical Data ◽  
Crime Data ◽  
Data Collection And Analysis ◽  
Criminal Penalties

The author analyzes three types of crime relapse existing in Latvia as well as paying attention on the fact that the crime data collection currently is not practiced in this country, although the level of the crime relapse reflects the effectiveness of applied criminal penalties. Statistical data collection and analysis of crime relapse could determine the effectiveness of criminal penalties as well as showing the usefulness of crime relapse reduction.

scholarly journals Performance indicators and standards for Polish research libraries

2009 ◽  
Vol 27 (87) ◽  
pp. 17-28
Author(s):  
Lidia Derfer-Wolf ◽  
Ewa Dobrzynska-Lankosz ◽  
Wanda Dziadkiewicz ◽  
Miroslaw Gorny ◽  
Elzbieta Gorska ◽  
...  
Keyword(s):  
Data Collection ◽  
Performance Indicators ◽  
Statistical Data ◽  
Political Transformation ◽  
Research Libraries ◽  
Data Collection And Analysis ◽  
The Social ◽  
Library Evaluation

The article discusses proposed standards for Polish research libraries evaluation. At the beginning, the authors present the situation of research libraries in Poland. They write about the effects of the social-political transformation in the 90s, present selected statistical data, and describe the progress in computerisation. The following part of the article relates to the currently applied in Poland standards of library evaluation. Discussed are e.g. the presently applied tools for data collection and analysis. The last part includes proposed methods for the preparation of standards and assessments for Polish research libraries.

Integration of statistical and administrative agricultural data from Namibia

2021 ◽  
pp. 1-22
Author(s):  
Emily Berg ◽  
Johgho Im ◽  
Zhengyuan Zhu ◽  
Colin Lewis-Beck ◽  
Jie Li
Keyword(s):  
Measurement Error ◽  
Data Collection ◽  
Administrative Data ◽  
Statistical Data ◽  
Data Sources ◽  
Extension Programs ◽  
Multiple Data ◽  
Administrative Agencies ◽  
Crop Area ◽  
Using Data

Statistical and administrative agencies often collect information on related parameters. Discrepancies between estimates from distinct data sources can arise due to differences in definitions, reference periods, and data collection protocols. Integrating statistical data with administrative data is appealing for saving data collection costs, reducing respondent burden, and improving the coherence of estimates produced by statistical and administrative agencies. Model based techniques, such as small area estimation and measurement error models, for combining multiple data sources have benefits of transparency, reproducibility, and the ability to provide an estimated uncertainty. Issues associated with integrating statistical data with administrative data are discussed in the context of data from Namibia. The national statistical agency in Namibia produces estimates of crop area using data from probability samples. Simultaneously, the Namibia Ministry of Agriculture, Water, and Forestry obtains crop area estimates through extension programs. We illustrate the use of a structural measurement error model for the purpose of synthesizing the administrative and survey data to form a unified estimate of crop area. Limitations on the available data preclude us from conducting a genuine, thorough application. Nonetheless, our illustration of methodology holds potential use for a general practitioner.

Development of a DNP measurement grid to increase the rigor of doctor of nursing practice students' data collection and analysis methods

2020 ◽  
Vol 36 (6) ◽  
pp. 666-672
Author(s):  
Linda L. Costa ◽  
Debra Bingham ◽  
Carla L. Storr ◽  
Margaret Hammersla ◽  
Jeffrey Martin ◽  
...  
Keyword(s):  
Data Collection ◽  
Nursing Practice ◽  
Doctor Of Nursing Practice ◽  
Analysis Methods ◽  
Data Collection And Analysis

scholarly journals Loneliness Among the Elderly in Rural Contexts: A Mixed-Method Study Protocol

2021 ◽  
Vol 20 ◽  
pp. 160940692199686
Author(s):  
Borja Rivero Jiménez ◽  
David Conde-Caballero ◽  
Lorenzo Mariano Juárez
Keyword(s):  
Data Collection ◽  
Mixed Method ◽  
Rural Areas ◽  
Population Group ◽  
The Elderly ◽  
Interaction Patterns ◽  
Structured Interviews ◽  
Strict Adherence ◽  
Data Collection And Analysis ◽  
Technological Tools

Loneliness among the elderly has become a pressing issue in Western societies. In the Spanish context, the problem of the so-called “empty” Spain disproportionately affects this population group—elderly individuals living in rural areas with low population density, and therefore at higher risk of social exclusion and isolation. We introduce here a mixed-method, quantitative-qualitative research protocol, triangulated with technological tools, designed to improve both data acquisition and subsequent data analysis and interpretation. This study will take place in a rural locality in the Extremadura region (Spain), chosen according to a particular socio-demographic profile. The De Jong Gierveld Loneliness Scale will be used on a cohort of 80 people over 65 years old. Within this cohort, a smaller sample of 20–30 individuals will be selected for semi-structured interviews about their beliefs and experiences of loneliness. Finally, data gathered from technological tools (smartbands, Bluetooth sensors) will allow us to monitor social interactions and to map daily loneliness/interaction patterns. Data will be triangulated by analyzing and comparing the empirical material gathered through these different methods and tools. Strict adherence to ethical standards for data protection and handling will be essential through data collection and analysis. As well as providing insights into the phenomenon of loneliness in old age, the use of different methods and tools for data collection will provide the basis for an epistemological reflection on the scope and limits of each one of these methods.

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