scholarly journals Who Pays? Measuring Differences in the Process of Repayment of Legal Financial Obligations

2021 ◽  
Vol 10 (11) ◽  
pp. 433
Author(s):  
Kathleen Powell
Keyword(s):  
Logistic Regression ◽  
Institutional Context ◽  
Policy Implications ◽  
Debt Repayment ◽  
Financial Obligations ◽  
Financial Obligation

This study identifies the correlates of legal financial obligation (LFO) debt repayment among persons sentenced to probation and transferred to a specialized collections unit. Using bivariate tests and logistic regression, results indicate that starting balance amounts, monthly payment amounts, and enforcement actions (capias warrant) are the strongest influences on the likelihood of full debt repayment. These results indicate that some persons will struggle to repay their LFO balances if amounts assessed are in excess of their means, even in an institutional context adopting an individualized, flexible, and non-punitive approach to collections. Policy implications suggest a need for reform at the point of LFO assessment to avoid imposing obligations that are unreasonable to individuals’ ability to repay.

Analysis on application level based on ordinal logistic regression and best of advanced manufacturing technologies (AMT) selection based on fuzzy-TOPSIS integration approach

2021 ◽  
pp. 1-11
Author(s):  
Guilian Wang ◽  
Liyan Zhang ◽  
Jing Guo
Keyword(s):  
Logistic Regression ◽  
Organizational Factors ◽  
Fuzzy Topsis ◽  
Ordinal Logistic Regression ◽  
Industrial Robots ◽  
Policy Implications ◽  
Market Pricing ◽  
Factors Affecting ◽  
Pricing Power ◽  
The Core Competence

This paper try to fully reveal the key factors affecting the the level of AMT application in micro- and small enterprises (MSEs) from its organizational factors by ordinal logistic regression. The results show that MSEs have a relatively high level of AMT application as a whole due to the maturity and cost reduction of basic technologies such as artificial intelligence, digital manufacturing and industrial robots. In this paper we propose manufacturing world analysis at Application using Logistic Regression and best AMT selection using Fuzzy-TOPSIS Integration approach.Considering the influence mechanism of each factor, the important factors that affect the application level of AMT are the enterprise’s market pricing power, the main production types, technical, market and management capabilities, organization development incentives and the interaction with external stakeholders. Based on the results above, the following policy implications are proposed: further expanding the customized production in MSEs to gradually improve the market pricing power, expanding the core competence of enterprises, enhancing the employee autonomy, and strengthening the interaction with industry organizations.

scholarly journals Evaluating working conditions in the informal economy: Evidence from the 2015 European Working Conditions Survey

2019 ◽  
Vol 34 (3) ◽  
pp. 281-306 ◽  
Author(s):  
Colin C Williams ◽  
Ioana Alexandra Horodnic
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Working Conditions ◽  
Logistic Regression Analysis ◽  
Informal Economy ◽  
Mixed Effects ◽  
Policy Implications ◽  
Formal Economy ◽  
European Working ◽  
European Working Conditions Survey

Although it is widely held that working conditions in the informal economy are worse than in the formal economy, little evidence has been so far provided. The aim of this article is to fill this lacuna by comparing the working conditions of informal employees with formal employees using the 2015 European Working Conditions Survey. Multilevel mixed-effects logistic regression analysis provides a nuanced and variegated appreciation of which working conditions are worse for informal employees, which are no different, and which are better for informal than formal employees. The article concludes by discussing the theoretical and policy implications.

scholarly journals Work-environmental determinants of mass fainting illness among textile factory workers

2019 ◽  
Vol 34 (2) ◽  
pp. 112-122
Author(s):  
Maly Phy ◽  
Twisuk Pungpeng ◽  
Chaweewon Boonshuyar ◽  
Thanu Chartananondh
Keyword(s):  
Logistic Regression ◽  
Preventive Measure ◽  
Cross Sectional Study ◽  
Screening Instrument ◽  
Policy Implications ◽  
Environmental Determinants ◽  
Factory Workers ◽  
Cross Sectional ◽  
Content Type ◽  
The Government

Purpose The purpose of this paper is to develop a brief screening instrument to identify risk factors of factory workers experiencing mass fainting illness (MFI) due to work-environmental determinants. Design/methodology/approach A factory-based cross-sectional study was conducted among 740 workers in October 2017 and was completed with face-to-face interviews. Data analyses included univariate logistic regression, backward stepwise linear regression and multiple logistic regression. Sum scores on significant items and receiver operator characteristic curves were used to compute potential cut-off points and the sensitivity and specificity rates. Findings Significant work-environmental factors were identified as working at very high speeds, having less influence on the choice of working partners, perceived high temperature at work, having less opportunity to do their best at work, and concern about losing a job in the next six months. In developing a screening instrument, a 6.5 cut-off point that corresponded to 99.6 percent sensitivity and 92.2 percent specificity was identified. Originality/value The study concludes that this MFI-instrument could potentially be used to prevent MFI. By understanding the policy implications, the government body, employers, workers, development partners and stakeholders should work toward preventing MFI. Implementing a preventive measure is therefore warranted due to the health education impact.

Bullets, Blades, and Being Afraid in Hispanic High Schools: An Exploratory Study of the Presence of Weapons and Fear of Weapon-Associated Victimization Among High School Students in a Border Town

2004 ◽  
Vol 50 (3) ◽  
pp. 372-394 ◽  
Author(s):  
Ben Brown ◽  
Wm. Reed Benedict
Keyword(s):  
High School ◽  
Logistic Regression ◽  
High School Students ◽  
High Schools ◽  
Exploratory Study ◽  
Policy Implications ◽  
Regression Analyses ◽  
School Students ◽  
Border Town ◽  
Language Spoken At Home

This article presents data obtained from a survey of high school students in Brownsville, Texas. Almost half of the students reported having seen other students carry knives at school, roughly 1 in 10 reported having seen other students carry guns at school, and more than 1 in 5 reported being fearful of weapon-associated victimization at school. Logistic regression analyses indicate that age, gender, seeing other students carry weapons, and involvement with student clubs/organizations significantly affect fear of weapon-associated victimization. Using language spoken at home as a measure of acculturation, it was also determined that immigrant juveniles are more fearful of weaponassociated victimization than nonimmigrant juveniles. The theoretical and policy implications of the findings are discussed.

scholarly journals Effects of Diabetes on The Output of Farmer and Its Policy Implications

2020 ◽  
Vol 15 (1) ◽  
pp. 1
Author(s):  
Syed Asif Ali Naqvi ◽  
Bilal Hussain ◽  
Syed Ale Raza Shah ◽  
Muhammad Sohail Amjad Makhdum
Keyword(s):  
Logistic Regression ◽  
Marital Status ◽  
Work Performance ◽  
Negative Influence ◽  
Policy Implications ◽  
Cross Sectional ◽  
Farming Communities ◽  
Regression Techniques ◽  
The Impact ◽  
Working Efficiency

This study investigated the impact of diabetes on work performance of different farming communities from Punjab, Pakistan. This study was based on cross-sectional data. A representative sample of 374 farmers was collected from five selected districts. Three types of respondents were analyzed in the study e.g.,laborer, small and large growers. Poisson and logistic regression techniques were used for the sake of analysis. According to the investigated results for thelabor category, respondents with more age, less qualification, low earning per month (Rupees), and having positive record of family diabetes, would havemore leave per month. In the same way, findings for small farmers revealed that education, family size, family with diabetic records, marital status and availability at farm (hour/day) were significant. In case of third category, study outcome highlighted that age, education, marital status, having positive record offamily diabetes and number of hours spent at farm would be positively correlated with the reduction in working efficiency at farm due to diabetes. It can beconcluded that diabetes have negative influence on the work performance of selected farming groups.

Predictors of Permanent Housing for Sheltered Homeless Families

1996 ◽  
Vol 77 (1) ◽  
pp. 50-57 ◽  
Author(s):  
Cynthia Rocha ◽  
Alice K. Johnson ◽  
Kay Young McChesney ◽  
William H. Butterfield
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
African American ◽  
African Americans ◽  
Family Size ◽  
Policy Implications ◽  
Homeless Families ◽  
Permanent Housing ◽  
The Family ◽  
Over Time

The authors analyze 10 years of data on homelessness to determine the characteristics of homeless families most likely to find permanent housing after leaving a shelter environment. They studied 1,156 families from 1983 to 1992 to determine where these families go after leaving the shelter and whether the pattern changed over time. Logistic regression analysis found that the larger the family size and being African American were factors that predicted a decreased likelihood of finding permanent housing. Families with one child were 1.5 times more likely to find permanent housing than were families with three children, and whites were 1.9 times more likely to find permanent housing than were African Americans. Furthermore, homeless shelter residents were five times more likely to find permanent housing in 1983 than in 1992, regardless of demographic predictors. Practice and policy implications are discussed.

scholarly journals ICT Adoption and the Digital Divide in Serbia: Factors and Policy Implications

10.28945/3247 ◽  
2008 ◽  
Author(s):  
Zlatko Kovacic ◽  
Dragan Vukmirovic
Keyword(s):  
Logistic Regression ◽  
Digital Divide ◽  
Predictive Accuracy ◽  
Classification Tree ◽  
Policy Implications ◽  
Individual Level ◽  
Internet Skills ◽  
Ict Adoption ◽  
Parsimonious Model ◽  
The Individual

This paper explores factors such as socio-demographics, income and wealth and e-skills that may influence the adoption of the ICTs at the individual level. We examine to what extent these factors contribute to the digital divide between different social groups in Serbia. We use the panel data from the survey “ICT usage in Republic of Serbia” in 2006 and 2007, covering over 3000 individuals/households, to perform a quantitative analysis of the digital divide and ICT adoption. Based on a classification tree and a logistic regression model, a profile of the typical ICT adopter and non-adopter is identified. The empirical results show the following: (i) the digital divide between age group 55-74 and those younger that 55 slightly increased in 2007 in case of regular Internet use; (ii) at the individual level the ICT adoption (use of PC, Internet and mobile phones) in Serbia is mainly influenced by the income and wealth of an individual, its computer and Internet skills and age; (iii) this result is quite robust across the methodological approaches used; and (iv) the classification tree approach is preferable since it gives the same predictive accuracy as the logistic regression with a more parsimonious model. The policy implications of these results are discussed.

Residential Stability Versus Residents’ Interactions: The Determinants of Voluntary Participation in Police Block Activity

2020 ◽  
Author(s):  
Jonathan E Coats
Keyword(s):  
Logistic Regression ◽  
Community Engagement ◽  
Crime Prevention ◽  
Survey Data ◽  
Policy Implications ◽  
Future Research ◽  
Voluntary Participation ◽  
Group Level ◽  
Residential Stability ◽  
Interaction Terms

Abstract This research examines the influence of residential stability and resident’s interactions on participation in police block activity. Community engagement is one approach used by the police to increase the co-production of crime prevention by providing opportunities and engaging the community in group-level informal and voluntary activities. These optional activities are designed to promote a working relationship between the residents and the police. Multilevel ordinal logistic regression was run to estimate participation in police block activity, using the Seattle Neighborhood and Crime Survey data. The results demonstrate two things. First, this study extends the standard variables, used in examining voluntary involvement, to the frequency of participation in police block activity. Secondly, using interaction terms between residential stability and between residents’ interactions, the results suggest that between residents’ interaction may be a better predictor of frequent participation in police block activity than homeownership or length of residency. Finally, policy implications and future research avenues are discussed.

scholarly journals The Effect of Various Police Enforcement Actions on Violent Crime: Evidence From a Saturation Foot-Patrol Intervention

2018 ◽  
Vol 29 (6-7) ◽  
pp. 611-629 ◽  
Author(s):  
Eric L. Piza
Keyword(s):  
Quality Of Life ◽  
Logistic Regression ◽  
Crime Prevention ◽  
Regression Models ◽  
Policy Implications ◽  
Target Area ◽  
Spatial Displacement ◽  
Foot Patrol ◽  
Logistic Regression Models

The current study tests the crime prevention effect of different police actions conducted during a foot-patrol saturation initiative in Newark, New Jersey. Police actions were categorized into two typologies: enforcement actions (i.e., arrests, quality of life summonses and field interrogations) and guardian actions (i.e., business checks, citizen contacts, bus checks, and taxi inspections). Logistic regression models tested the effect of enforcement and guardian actions on crime during daily (i.e., 24-hr) periods as well as the intervention’s operational (6:00 p.m.-2:00 a.m.) and nonoperational (2:00 a.m.-5:00 p.m.) periods. Analyses were conducted twice, once for the Operation Impact target area and once for a surrounding catchment zone (to measure spatial displacement). Findings suggest that guardian actions had a greater crime prevention effect than enforcement actions on crime occurrence. Policy implications of the findings are discussed.

Police Responses to Restraining Orders in Domestic Violence Incidents

2000 ◽  
Vol 27 (5) ◽  
pp. 561-580 ◽  
Author(s):  
ROBERT J. KANE
Keyword(s):  
Domestic Violence ◽  
Logistic Regression ◽  
Police Officers ◽  
Theoretical Framework ◽  
Policy Implications ◽  
Restraining Order ◽  
Restraining Orders ◽  
Police Responses ◽  
Risk Of Injury ◽  
Predictive Strength

The present analysis examines the extent to which police officers arrest domestic violence offenders who violate restraining orders. The study develops a theoretical framework, referred to as the custody-threshold thesis, that considers the decision to arrest to be a function of the officers' goals to satisfy one of several purposes of custody. Findings from logistic regression modeling show that restraining-order violations in domestic violence incidents have the greatest impact on arrest probability when risk of injury to the victim is low, but that as risk increases, the predictive strength of restraining-order violations diminishes. Findings support the custody-threshold thesis, suggesting important policy implications, which are identified and discussed.

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