Do New Chiefs Mean Fresh Perspectives? The Institutionalization of the Police Executive Environment

2021 ◽  
pp. 009385482110067
Author(s):  
Matthew C. Matusiak
Keyword(s):  
Law Enforcement ◽  
Regression Models ◽  
Ordinary Least Squares ◽  
Limited Attention ◽  
Control Group ◽  
Multivariate Methods ◽  
Environmental Perceptions ◽  
Police Organizations ◽  
Law Enforcement Agency ◽  
Time Periods

Research suggests policing is a highly institutionalized field. Limited attention has been paid, however, to the institutionalization of leaders’ views. Assessing turnover in 71 Texas police organizations between October, 2011, and July, 2015, this research evaluates whether there is consistency (i.e., institutional homogenization) after turnover in chiefs’ perceptions of their environments and agency priorities. The research is unique in that it assesses two chiefs’ perceptions that have both led the same law enforcement agency in successive time periods. Assessments of environment and priorities from former chiefs and those replacing them are evaluated utilizing descriptive, bivariate, and multivariate methods. These assessments are also compared with a control group of chiefs from agencies not experiencing turnover. Bivariate results suggest little variation across current and former chiefs, whereas ordinary least squares (OLS) regression models suggest differing relationships across chiefs groups between environmental perceptions and agency priorities. Discussion of the findings is framed by institutional theory.

Police cadet general and interactional knowledge of persons with autism spectrum disorders (ASDs)

2020 ◽  
Vol 43 (2) ◽  
pp. 345-359 ◽  
Author(s):  
Allen Copenhaver ◽  
Andrew S. Denney ◽  
Victoria Rapp
Keyword(s):  
Autism Spectrum Disorder ◽  
Law Enforcement ◽  
Regression Models ◽  
Ordinary Least Squares ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Policy Implications ◽  
General Knowledge ◽  
Content Type ◽  
Autism Knowledge

PurposeThe purpose of this study is to ascertain law enforcement cadet general knowledge of autism spectrum disorder (ASD) and practical knowledge in how to apply various aspects of their profession to persons with ASD.Design/methodology/approachIn total, 341 law enforcement cadet surveys administered across ten individual law enforcement cadet classes were analyzed via two individual ordinary least squares (OLS) regression models. These regression models were designed to predict changes in cadet scores on their (1) general knowledge of autism scale (i.e., general knowledge regarding autism spectrum disorder itself) and (2) interactional law enforcement knowledge of autism scale (i.e., how to apply various aspects of their job to persons with ASD).FindingsFindings show that cadets who had a stronger confidence in their ability to interact with persons who have ASD actually knew less than their counterparts with lower reported overall confidence. However, one's confidence in their ability to identify persons with ASD was associated with having better overall general knowledge of ASD itself. Similarly, the greater one's overall confidence in interacting with persons with ASD was associated with lower interactional knowledge. In each model, general autism knowledge and interactional knowledge were positively associated.Practical implicationsThe results of this study have implications for cadet and officer training on ASD as each need to be trained in both general knowledge of autism and interactional autism knowledge skills related to the job functions of being a LEO. Policy implications and directions for future research are discussed.Originality/valueThe literature is sparse on law enforcement knowledge of and interaction with persons who have ASD. As such, this study has the potential to make a strong impact on the literature regarding law enforcement and their knowledge and/or interactions with persons who have ASD.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

scholarly journals A Method for Assessing Threats to the Economic Security of a Region: A Case Study of Public Procurement in Russia

Risks ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 10
Author(s):  
Valentina Kravchenko ◽  
Tatiana Kudryavtseva ◽  
Yuriy Kuporov
Keyword(s):  
Regression Models ◽  
Public Procurement ◽  
Ordinary Least Squares ◽  
Economic Security ◽  
Government Procurement ◽  
Security Monitoring ◽  
Significant Relationships ◽  
Monitoring Tools ◽  
Russian Region

The issue of economic security is becoming an increasingly urgent one. The purpose of this article is to develop a method for assessing threats to the economic security of the Russian region. This method is based on step-by-step actions: first of all, choosing an element of the region’s economic security system and collecting its descriptive indicators; then grouping indicators by admittance-process-result categories and building hypotheses about their influence; testing hypotheses using a statistical package and choosing the most significant connections, which can pose a threat to the economic security of the region; thereafter ranking regions by the level of threats and developing further recommendations. The importance of this method is that with the help of grouping regions (territory of a country) based on proposed method, it is possible to develop individual economic security monitoring tools. As a result, the efficiency of that country’s region can be higher. In this work, the proposed method was tested in the framework of public procurement in Russia. A total of 14 indicators of procurement activity were collected for each region of the Russian Federation for the period from 2014 to 2018. Regression models were built on the basis of the grouped indicators. Ordinary Least Squares (OLS) Estimation was used. As a result of pairwise regression models analysis, we have defined four significant relationships between public procurement indicators. There are positive connections between contracts that require collateral and the percentage of tolerances, between the number of bidders and the number of regular suppliers, between the number of bidders and the average price drop, and between the number of purchases made from a single supplier and the number of contracts concluded without reduction. It was determined that the greatest risks for the system were associated with the connection between competition and budget savings. It was proposed to rank analyzed regions into four groups: ineffective government procurement, effective government procurement, and government procurement that threatens the system of economic security of the region, that is, high competition with low savings and low competition with high savings. Based on these groups, individual economic security monitoring tools can be developed for each region.

Medicaid Not Required to Fund Medically Necessary Abortions

1980 ◽  
Vol 1 (8) ◽  
pp. 3-6
Author(s):  
George J. Annas
Keyword(s):  
United States ◽  
Law Enforcement ◽  
United States Supreme Court ◽  
The United States ◽  
United States Constitution ◽  
Medical Procedures ◽  
Poor Women ◽  
Law Enforcement Agency ◽  
The Individual ◽  
Joint Resolution

In an extraordinary and highly controversial 5-4 decision, the United States Supreme Court decided on June 30, 1980, that the United States Constitution does not require either the federal government or the individual states to fund medically necessary abortions for poor women who qualify for Medicaid.At issue in this case is the constitutionality of the Hyde Amendment. The applicable 1980 version provides:|N]one of the funds provided by this joint resolution shall be used to perform abortions except where the life of the mother would be endangered if the fetus were carried to term; or except for such medical procedures necessary for the victims of rape or incest when such rape or incest has been reported promptly to a law enforcement agency or public health service, (emphasis supplied)

scholarly journals Serum Zinc, Copper, and Other Biometals Are Associated with COVID-19 Severity Markers

Metabolites ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 244
Author(s):  
Anatoly V. Skalny ◽  
Peter S. Timashev ◽  
Michael Aschner ◽  
Jan Aaseth ◽  
Lyubov N. Chernova ◽  
...  
Keyword(s):  
Disease Severity ◽  
Regression Models ◽  
Serum Zinc ◽  
Lung Damage ◽  
Severe Illness ◽  
Control Group ◽  
C Reactive Protein ◽  
Significant Group ◽  
Reactive Protein ◽  
Metal Levels

The objective of the present study was to evaluate of serum metal levels in COVID-19 patients with different disease severity, and to investigate the independent association between serum metal profile and markers of lung damage. The cohort of COVID-19 patients consisted of groups of subjects with mild, moderate, and severe illness, 50 examinees each. Forty-four healthy subjects of the respective age were involved in the current study as the control group. Serum metal levels were evaluated using inductively-coupled plasma mass-spectrometry. Examination of COVID-19 patients demonstrated that heart rate, respiratory rate, body temperature, C-reactive protein levels, as well as lung damage increased significantly with COVID-19 severity, whereas SpO2 decreased gradually. Increasing COVID-19 severity was also associated with a significant gradual decrease in serum Ca, Fe, Se, Zn levels as compared to controls, whereas serum Cu and especially Cu/Zn ratio were elevated. No significant group differences in serum Mg and Mn levels were observed. Serum Ca, Fe, Se, Zn correlated positively with SpO2, being inversely associated with fever, lung damage, and C-reactive protein concentrations. Opposite correlations were observed for Cu and Cu/Zn ratio. In regression models, serum Se levels were inversely associated with lung damage independently of other markers of disease severity, anthropometric, biochemical, and hemostatic parameters. Cu/Zn ratio was also considered as a significant predictor of lower SpO2 in adjusted regression models. Taken together, these findings demonstrated that metal metabolism significantly interferes with COVID-19 pathogenesis, although the causal relations as well as precise mechanisms are yet to be characterized.

Alcoholism and Law Enforcement

1963 ◽  
Vol 9 (1) ◽  
pp. 84-88 ◽  
Author(s):  
Robert F. Borkenstein
Keyword(s):  
Law Enforcement ◽  
Antisocial Behavior ◽  
Public Safety ◽  
Criminal Code ◽  
Alcoholic Beverages ◽  
General Law ◽  
Law Enforcement Agency

The responsibility of the progressive law enforcement agency is to gain compliance with laws that promote harmony in society. Alcohol tends ,to alter the attitudes of otherwise law-abiding citizens so that there is a high correlation between the excessive use of alcohol and antisocial behavior. Laws in the criminal code dealing with alcohol fall roughly into four categories—those dealing directly with public safety, those that reflect moral at titudes, those reflecting the attitudes of loud minorities, and those dealing with the licensing, revenue, or sale of alcoholic beverages. From the standpoint of the general law enforcement agency, the only laws worthy of energetic enforcement are those dealing with public safety. The others are usually enforced by agencies with special and limited jurisdiction.

How local personal vote-earning attributes affect the aggregate party vote share: Evidence from the Belgian flexible-list PR system (2003–2014)

Politics ◽  
2018 ◽  
Vol 39 (4) ◽  
pp. 464-479
Author(s):  
Gert-Jan Put ◽  
Jef Smulders ◽  
Bart Maddens
Keyword(s):  
Regression Models ◽  
Empirical Test ◽  
Original Data ◽  
Ordinary Least Squares ◽  
Vote Share ◽  
District Level ◽  
National Party ◽  
Data Set ◽  
Geographically Distributed ◽  
Party Vote Shares

This article investigates the effect of candidates exhibiting local personal vote-earning attributes (PVEA) on the aggregate party vote share at the district level. Previous research has often assumed that packing ballot lists with localized candidates increases the aggregate party vote and seat shares. We present a strict empirical test of this argument by analysing the relative electoral swing of ballot lists at the district level, a measure of change in party vote shares which controls for the national party trend and previous party results in the district. The analysis is based on data of 7527 candidacies during six Belgian regional and federal election cycles between 2003 and 2014, which is aggregated to an original data set of 223 ballot lists. The ordinary least squares (OLS) regression models do not show a significant effect of candidates exhibiting local PVEA on relative electoral swing of ballot lists. However, the results suggest that ballot lists do benefit electorally if candidates with local PVEA are geographically distributed over different municipalities in the district.

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