scholarly journals Sentencing consistency in the New Zealand District Courts

2021 ◽  
Author(s):  
◽  
Wayne Goodall

<p>This thesis examines the consistency of sentencing between the circuits of the New Zealand District Courts. Four predictions based on a sequence or chain of theories incorporating the concept of bounded rationality from decision making theory, the influence of formal and substantive rationalities on sentencing decisions, court community theory, and personal construct psychology were tested. The circuit in which sentencing took place was expected to affect the likelihood of incarceration and to affect the length of incarceration. If these predictions were met, it was further predicted that the weight applied to some or all of the sentencing factors would vary between circuits. It is understood to be the first study controlling for a wide range of sentencing factors examining the consistency of sentencing between locations in New Zealand and one of the first from anywhere outside of the United States. The four predictions were tested using sentencing data from the two years 2008-2009 for three high volume offences (aggravated drink driving, male assaults female and burglary). Sentencing was treated as a two part decision process, with the selection of a sentence type followed by the determination of the sentence amount. Each prediction was separately modelled for each offence. Different types of model were chosen as being more suitable for the specific predictions: logistic regression for the likelihood of incarceration; linear regression for the length of incarceration; multi-level generalised linear regression with random co-efficients to determine if the weight applied to specific factors varied by circuit in the determination of whether or not to incarcerate; and multi-level linear regression with random co-efficients to determine if the weight applied to specific factors varied by circuit in the determination of sentence length. The logistic regression and linear regression models demonstrated that there were statistically significant and substantively significant differences between circuits in the likelihood and length of incarceration. The extent of inconsistency varied by offence type with the most marked differences occurring for aggravated drink driving and burglary. Offence seriousness and criminal history factors were found to be the principal influences on both sentence decisions for all three offences. The multi-level models for aggravated drink driving and burglary revealed a core of seriousness and criminal history factors whose influence varied across the circuits. The models for male assaults female were less informative, highlighting the likelihood that these models were limited by the omission of key sentencing variables and the narrow scope of this particular assault type within the wider spectrum of assaults. The findings should not be interpreted as if they are a critique of the sentence imposed in any individual case or of the sentencing by any judge or in any circuit. It is a critique of sentencing guidance in New Zealand and its ability to achieve a fundamental tenet of justice: the similar treatment of similar offenders being sentenced in similar circumstances. In addition to testing the predictions the multi-level models were extended to address whether the observed variation in sentencing was associated with variations in circuit context. Due to the limited number of circuits (17) and multi-collinearity between the contextual variables, bivariate analyses had to be employed. The modelling revealed a consistent difference between provincial and metropolitan circuits; the two categories of circuit were distinguished from one another by many of the other more specific variables that had a significant association with sentencing approaches. The provincial circuits were more likely to incarcerate and to impose longer sentences. However, the small number of circuits and multi-collinearity between the variables precluded more detailed analysis to identify which of the contextual variables distinguishing metropolitan and provincial circuits had the greatest influence. These findings have significant implications for the judiciary and for sentencing policy makers. Urgent attention should be given to addressing opportunities to increase the availability of sentencing guidance to reduce the degree of inconsistency. More detailed offence based sentencing guidance is required; in the current context there are two options that could be used. The Court of Appeal could issue a broader range of guideline judgments or the legislation for the Sentencing Council and the process for developing and promulgating guidelines could be implemented. For logistical and public policy reasons the Sentencing Council approach is preferred. There is a risk that failure to address the levels of inconsistency will result in the sentencing system falling into disrepute.</p>

2021 ◽  
Author(s):  
◽  
Wayne Goodall

<p>This thesis examines the consistency of sentencing between the circuits of the New Zealand District Courts. Four predictions based on a sequence or chain of theories incorporating the concept of bounded rationality from decision making theory, the influence of formal and substantive rationalities on sentencing decisions, court community theory, and personal construct psychology were tested. The circuit in which sentencing took place was expected to affect the likelihood of incarceration and to affect the length of incarceration. If these predictions were met, it was further predicted that the weight applied to some or all of the sentencing factors would vary between circuits. It is understood to be the first study controlling for a wide range of sentencing factors examining the consistency of sentencing between locations in New Zealand and one of the first from anywhere outside of the United States. The four predictions were tested using sentencing data from the two years 2008-2009 for three high volume offences (aggravated drink driving, male assaults female and burglary). Sentencing was treated as a two part decision process, with the selection of a sentence type followed by the determination of the sentence amount. Each prediction was separately modelled for each offence. Different types of model were chosen as being more suitable for the specific predictions: logistic regression for the likelihood of incarceration; linear regression for the length of incarceration; multi-level generalised linear regression with random co-efficients to determine if the weight applied to specific factors varied by circuit in the determination of whether or not to incarcerate; and multi-level linear regression with random co-efficients to determine if the weight applied to specific factors varied by circuit in the determination of sentence length. The logistic regression and linear regression models demonstrated that there were statistically significant and substantively significant differences between circuits in the likelihood and length of incarceration. The extent of inconsistency varied by offence type with the most marked differences occurring for aggravated drink driving and burglary. Offence seriousness and criminal history factors were found to be the principal influences on both sentence decisions for all three offences. The multi-level models for aggravated drink driving and burglary revealed a core of seriousness and criminal history factors whose influence varied across the circuits. The models for male assaults female were less informative, highlighting the likelihood that these models were limited by the omission of key sentencing variables and the narrow scope of this particular assault type within the wider spectrum of assaults. The findings should not be interpreted as if they are a critique of the sentence imposed in any individual case or of the sentencing by any judge or in any circuit. It is a critique of sentencing guidance in New Zealand and its ability to achieve a fundamental tenet of justice: the similar treatment of similar offenders being sentenced in similar circumstances. In addition to testing the predictions the multi-level models were extended to address whether the observed variation in sentencing was associated with variations in circuit context. Due to the limited number of circuits (17) and multi-collinearity between the contextual variables, bivariate analyses had to be employed. The modelling revealed a consistent difference between provincial and metropolitan circuits; the two categories of circuit were distinguished from one another by many of the other more specific variables that had a significant association with sentencing approaches. The provincial circuits were more likely to incarcerate and to impose longer sentences. However, the small number of circuits and multi-collinearity between the variables precluded more detailed analysis to identify which of the contextual variables distinguishing metropolitan and provincial circuits had the greatest influence. These findings have significant implications for the judiciary and for sentencing policy makers. Urgent attention should be given to addressing opportunities to increase the availability of sentencing guidance to reduce the degree of inconsistency. More detailed offence based sentencing guidance is required; in the current context there are two options that could be used. The Court of Appeal could issue a broader range of guideline judgments or the legislation for the Sentencing Council and the process for developing and promulgating guidelines could be implemented. For logistical and public policy reasons the Sentencing Council approach is preferred. There is a risk that failure to address the levels of inconsistency will result in the sentencing system falling into disrepute.</p>


1994 ◽  
Vol 12 (5) ◽  
pp. 747-749 ◽  
Author(s):  
Moises Kaweblum ◽  
Maria Del Carmen Aguilar ◽  
Eduardo Blancas ◽  
Jaime Kaweblum ◽  
Wallace B. Lehman ◽  
...  

Metals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 18
Author(s):  
Rahel Jedamski ◽  
Jérémy Epp

Non-destructive determination of workpiece properties after heat treatment is of great interest in the context of quality control in production but also for prevention of damage in subsequent grinding process. Micromagnetic methods offer good possibilities, but must first be calibrated with reference analyses on known states. This work compares the accuracy and reliability of different calibration methods for non-destructive evaluation of carburizing depth and surface hardness of carburized steel. Linear regression analysis is used in comparison with new methods based on artificial neural networks. The comparison shows a slight advantage of neural network method and potential for further optimization of both approaches. The quality of the results can be influenced, among others, by the number of teaching steps for the neural network, whereas more teaching steps does not always lead to an improvement of accuracy for conditions not included in the initial calibration.


Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 853
Author(s):  
Jee-Yun Kim ◽  
Jeong Yee ◽  
Tae-Im Park ◽  
So-Youn Shin ◽  
Man-Ho Ha ◽  
...  

Predicting the clinical progression of intensive care unit (ICU) patients is crucial for survival and prognosis. Therefore, this retrospective study aimed to develop the risk scoring system of mortality and the prediction model of ICU length of stay (LOS) among patients admitted to the ICU. Data from ICU patients aged at least 18 years who received parenteral nutrition support for ≥50% of the daily calorie requirement from February 2014 to January 2018 were collected. In-hospital mortality and log-transformed LOS were analyzed by logistic regression and linear regression, respectively. For calculating risk scores, each coefficient was obtained based on regression model. Of 445 patients, 97 patients died in the ICU; the observed mortality rate was 21.8%. Using logistic regression analysis, APACHE II score (15–29: 1 point, 30 or higher: 2 points), qSOFA score ≥ 2 (2 points), serum albumin level < 3.4 g/dL (1 point), and infectious or respiratory disease (1 point) were incorporated into risk scoring system for mortality; patients with 0, 1, 2–4, and 5–6 points had approximately 10%, 20%, 40%, and 65% risk of death. For LOS, linear regression analysis showed the following prediction equation: log(LOS) = 0.01 × (APACHE II) + 0.04 × (total bilirubin) − 0.09 × (admission diagnosis of gastrointestinal disease or injury, poisoning, or other external cause) + 0.970. Our study provides the mortality risk score and LOS prediction equation. It could help clinicians to identify those at risk and optimize ICU management.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1953.3-1953
Author(s):  
J. Guo ◽  
W. Zhou ◽  
M. He ◽  
Z. Gu ◽  
C. Dong

Background:Fatigue of chronic diseases has been paid more and more attention. but the status of fatigue in gout patients has not been reported all the world[1].Objectives:In the absence of previous studies, our study aims to investigate the fatigue status, explore the potential predictors of fatigue and the effects of fatigue on health-related quality of life (HRQoL) among Chinese gout patients.Methods:This cross-sectional study was conducted from the Affiliated Hospital of Nantong University. A series of questionnaires were applied: Fatigue Scale-14 (FS-14), the 10 cm visual analog scale (VAS), the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder questionnaire (GAD-7), the Pittsburgh Sleep Quality Index (PSQI), Health Assessment Questionnaire(HAQ), the Short Form 36 health survey (SF-36). Laboratory examinations were taken to obtain some biochemical indicators. Independent samples t-test, Mann–Whitney U-test, Chi-square analysis, Pearson /Spearman correlation, Stepwise linear regression and binary logistic regression were used to analyze the data.Results:411 gout patients were included in this study. Among them, more than 50% patients reported physical fatigue in FS-14, severe disease, poor psychological status and reduced HRQoL were associated with fatigue. Multiple stepwise linear regression and binary logistic regression were applied and showed that pain, sleep quality, anxiety, depression and functional disorder were the potential predictors of fatigue. In addition, we found that the more severe the fatigue, the lower the patient’s HRQoL.Conclusion:Fatigue among gout patients is exceedingly common. The results of this study suggested that rheumatologists should pay closely attention to gout patients who suffer from serious fatigue, especially those with pain, poorer sleep quality, anxiety, depression and functional disorder.References:[1]Henry, A., Tourbah, A., Camus, G., Deschamps, R., Mailhan, L., Castex, C., Gout, O. & Montreuil, M. (2019) Anxiety and depression in patients with multiple sclerosis: The mediating effects of perceived social support, Multiple sclerosis and related disorders. 27, 46-51.Disclosure of Interests:None declared


2017 ◽  
Vol 11 (1) ◽  
pp. 77-98 ◽  
Author(s):  
Lopamudra D. Satpathy ◽  
Bani Chatterjee ◽  
Jitendra Mahakud

Measurement of the productivity of firms is an important research issue in productivity literature. Over the years, various methods have been developed to measure firm productivity across the globe. But there is no unanimity on the use of methods, and research on the identification of factors which determine productivity has been neglected. In view of these gaps, this study aims to measure total factor productivity (TFP) and tries to identify firm-specific factors which determine productivity of Indian manufacturing companies. The study is based on data of 616 firms from 1998–99 to 2012–13. To measure TFP, the Levinsohn–Petrin (L-P) method has been employed, and the fully modified ordinary least squares (FMOLS) method has been used to identify factors that affect TFP. The results reveal that embodied and disembodied technology plays a crucial role in the determination of productivity overall in manufacturing and other sub-industries. Similarly, the size of firms and intensity of raw material imports are also important for the determination of productivity across the sub-industries. JEL Classification: C14, C33, D24, L60


BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e037362
Author(s):  
Ben Wamamili ◽  
Mark Wallace-Bell ◽  
Ann Richardson ◽  
Randolph C Grace ◽  
Pat Coope

ObjectiveIn March 2011, New Zealand (NZ) launched an aspirational goal to reduce smoking prevalence to 5% or less by 2025 (Smokefree 2025 goal). Little is known about university students’ awareness of, support for and perceptions about this goal. We sought to narrow the knowledge gap.SettingUniversity students in NZ.MethodsWe analysed data from a 2018 cross-sectional survey of university students across NZ. Logistic regression analysis examined the associations between responses about the Smokefree goal with smoking and vaping, while controlling for age, sex and ethnicity. Confidence intervals (95% CI) were reported where appropriate.ParticipantsThe sample comprised 1476 students: 919 (62.3%) aged 18 to 20 and 557 (37.7%) aged 21 to 24 years; 569 (38.6%) male and 907 (61.4%) female; 117 (7.9%) Māori and 1359 (92.1%) non-Māori. Of these, 10.5% currently smoked (ie, smoked at least monthly) and 6.1% currently vaped (ie, used an e-cigarette or vaped at least once a month).ResultsOverall awareness of the Smokefree goal was 47.5% (95% CI: 44.9 to 50.1); support 96.9% (95% CI: 95.8 to 97.8); belief that it can be achieved 88.8% (95% CI: 86.8 to 90.7) and belief that e-cigarettes/vaping can help achieve it 88.1% (95% CI: 86.0 to 89.9).Dual users of tobacco cigarettes and e-cigarettes had greater odds of being aware of the Smokefree goal (OR=3.07, 95% CI: 1.19 to 7.92), current smokers had lower odds of supporting it (OR=0.13, 95% CI: 0.06 to 0.27) and of believing that it can be achieved (OR=0.15, 95% CI: 0.09 to 0.24) and current vapers had greater odds of believing that e-cigarettes/vaping can help to achieve it (OR=8.57, 95% CI: 1.18 to 62.52) compared with non-users.ConclusionsThe results suggest strong overall support for the Smokefree goal and belief that it can be achieved and that e-cigarettes/vaping can help achieve it. Smoking and vaping were associated with high awareness of the Smokefree goal, but lower support and optimism that it can be achieved.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wolf Ramackers ◽  
Julia Victoria Stupak ◽  
Indra Louisa Marcheel ◽  
Annette Tuffs ◽  
Harald Schrem ◽  
...  

Abstract Background Students’ ratings of bedside teaching courses are difficult to evaluate and to comprehend. Validated systematic analyses of influences on students’ perception and valuation of bedside teaching can serve as the basis for targeted improvements. Methods Six hundred seventy-two observations were conducted in different surgical departments. Survey items covered the categories teacher’s performance, student’s self-perception and organizational structures. Relevant factors for the student overall rating were identified by multivariable linear regression after exclusion of variable correlations > 0.500. The main target for intervention was identified by the 15% worst overall ratings via multivariable logistic regression. Results According to the students the success of bedside teaching depended on their active participation and the teacher’s explanations of pathophysiology. Further items are both relevant to the overall rating and a possible negative perception of the session. In comparison, negative perception of courses (worst 15%) is influenced by fewer variables than overall rating. Variables that appear in both calculations show slight differences in their weighing for their respective endpoints. Conclusion Relevant factors for overall rating and negative perception in bedside teaching can be identified by regression analyses of survey data. Analyses provide the basis for targeted improvement.


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