scholarly journals Criminal Record Relief for Human Trafficking Survivors: Analysis of Current State Statutes and the Need for a Federal Model Statute

2021 ◽  
pp. 473
Author(s):  
Ashleigh Pelto
Keyword(s):  
Best Practices ◽  
Human Trafficking ◽  
Best Practice ◽  
Evaluation Criteria ◽  
Report Cards ◽  
Criminal Record ◽  
State Report Cards ◽  
Current State ◽  
State Statutes ◽  
Trafficking Victims

This Note defines criminal record relief and analyzes the effectiveness of three state criminal record relief statutes at protecting trafficking survivors. This analysis is based on State Report Cards: Grading Criminal Record Relief Laws for Survivors of Human Trafficking by Polaris, a leading human trafficking nonprofit. It next discusses the absence of federal criminal record relief and how a statute at the federal level could provide relief for survivors with federal convictions while simultaneously providing a model for states to ensure their statutes incorporate best practices for record relief moving forward. This Note then discusses how Polaris’s report stops short of providing a model statute for states to draw from. Finally, this Note provides a best practice statute based on Polaris’s evaluation criteria and recommends it be added as an amendment to the Trafficking Victims Protection Act.

Review of the Current State and Future Development in Standardising Artificial Lighting

2019 ◽  
pp. 4-44 ◽  
Author(s):  
Peter Thorns
Keyword(s):  
Internet Of Things ◽  
Future Development ◽  
Best Practice ◽  
The Internet ◽  
Artificial Lighting ◽  
Current State ◽  
Internal Structures ◽  
European Regulations ◽  
The Internet Of Things

This paper discusses the organisations involved in the development of application standards, European regulations and best practice guides, their scope of work and internal structures. It considers their respective visions for the requirements for future standardisation work and considers in more detail those areas where these overlap, namely human centric or integrative lighting, connectivity and the Internet of Things, inclusivity and sustainability.

PROFESSIONAL TRAINING OF ELECTRONICS ENGINEERS: APPLYING US EXPERICENCE TO UKRAINAN HIGHER EDUCATION INSTITUTIONS

2020 ◽  
pp. 80-85
Author(s):  
Olha Pavlenko
Keyword(s):  
Higher Education ◽  
Education Research ◽  
Best Practices ◽  
Cost Reduction ◽  
Professional Training ◽  
Higher Education Institutions ◽  
Academic Staff ◽  
Research And Innovation ◽  
Current State

The article discusses the current state of professional training of engineers, in particular, electronics engineers in Ukrainian higher education institutions (HEIs) and explores best practices from US HEIs. The research outlines the features of professional training of electronics engineers and recent changes in Ukrainian HEIs. Such challenges for Ukrainian HEIs as lack of collaboration between higher education and science with industry, R&D cost reduction for HEIs, and downsizing the research and academic staff, the disparity between the available quality of human capital training and the demanded are addressed. The study attempts to identify successful practices of US HEIs professional training of engineers in order to suggest potential improvements in education, research, and innovation for training electronics engineers in Ukraine.

scholarly journals Fluctuating Asymmetry and Developmental Instability, a Guide to Best Practice

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 9
Author(s):  
John H. Graham
Keyword(s):  
Measurement Error ◽  
Best Practices ◽  
Environmental Stress ◽  
Fluctuating Asymmetry ◽  
Best Practice ◽  
Developmental Instability ◽  
The Past ◽  
Size Scaling ◽  
Research Designs

Best practices in studies of developmental instability, as measured by fluctuating asymmetry, have developed over the past 60 years. Unfortunately, they are haphazardly applied in many of the papers submitted for review. Most often, research designs suffer from lack of randomization, inadequate replication, poor attention to size scaling, lack of attention to measurement error, and unrecognized mixtures of additive and multiplicative errors. Here, I summarize a set of best practices, especially in studies that examine the effects of environmental stress on fluctuating asymmetry.

Measuring the Hidden Numbers of Human Trafficking Through Multiple Systems Estimation: Lessons Learned and Challenges Outstanding

2021 ◽  
pp. 001112872098719
Author(s):  
Davina Durgana ◽  
Jan van Dijk
Keyword(s):  
Human Trafficking ◽  
Migrant Workers ◽  
Lessons Learned ◽  
Multiple Systems ◽  
State Institutions ◽  
Gender And Age ◽  
Prevalence Estimates ◽  
Trafficking Victims ◽  
Developed Nations ◽  
Further Development

This article takes stock of studies conducted in eight countries to estimate the prevalence of human trafficking by employing the technique of Multiple Systems Estimation on data on victims of human trafficking recorded by state and non-state institutions. It presents an overview of MSE-based prevalence estimates of human trafficking victims per 100,000 inhabitants of these countries, disaggregated by type of exploitation, gender, and age. For some countries it also presents the different likelihoods of various sub-categories of trafficking victims, such as minors and migrant workers, to be detected by authorities and/or NGOs. Next, the article recounts what these studies have taught us about the suitability of applying MSE on existing multi-source databases to estimate the prevalence of trafficking victimization. The article concludes with a discussion on the promises and limitations of MSE and its prospects for further development, especially among developed nations.

Abstract 218: Expanding a Learning Collaborative Model in Chicago to Improve Door to Needle for Stroke Thrombolysis: Raising the Bar

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Shyam Prabhakaran ◽  
Renee M Sednew ◽  
Kathleen O’Neill
Keyword(s):  
Best Practices ◽  
Performance Improvement ◽  
Best Practice ◽  
Learning Collaborative ◽  
Collaborative Model ◽  
Stroke Registry ◽  
Chicago Area ◽  
Regional Collaboration ◽  
Content Expert ◽  
And Performance

Background: There remains significant opportunities to reduce door-to-needle (DTN) times for stroke despite regional and national efforts. In Chicago, Quality Enhancement for the Speedy Thrombolysis for Stroke (QUESTS) was a one year learning collaborative (LC) which aimed to reduce DTN times at 15 Chicago Primary Stroke Centers. Identification of barriers and sharing of best practices resulted in achieving DTN < 60 minutes within the first quarter of the 2013 initiative and has sustained progress to date. Aligned with Target: Stroke goals, QUESTS 2.0, funded for the 2016 calendar year, invited 9 additional metropolitan Chicago area hospitals to collaborate and further reduce DTN times to a goal < 45 minutes in 50% of eligible patients. Methods: All 24 hospitals participate in the Get With The Guidelines (GWTG) Stroke registry and benchmark group to track DTN performance improvement in 2016. Hospitals implement American Heart Association’s Target Stroke program and share best practices uniquely implemented at sites to reduce DTN times. The LC included a quality and performance improvement leader, a stroke content expert, site visits and quarterly meetings and learning sessions, and reporting of experiences and data. Results: In 2015, the year prior to QUESTS 2.0, the proportion of patients treated with tPA within 45 minutes of hospital arrival increased from 21.6% in Q1 to 31.4% in Q2. During the 2016 funded year, this proportion changed from 31.6% in Q1 to 48.3% in Q2. Conclusions: Using a learning collaborative model to implement strategies to reduce DTN times among 24 Chicago area hospitals continues to impact times. Regional collaboration, data sharing, and best practice sharing should be a model for rapid and sustainable system-wide quality improvement.

Increased adoption of best practices in ecological forecasting enables comparisons of forecastability across systems

2021 ◽  
Author(s):  
Abigail S. L. Lewis ◽  
Whitney M. Woelmer ◽  
Heather L. Wander ◽  
Dexter W. Howard ◽  
John W. Smith ◽  
...  
Keyword(s):  
Decision Support ◽  
Best Practices ◽  
Forecast Skill ◽  
Robust Analysis ◽  
Ecological Forecasting ◽  
Workflow Automation ◽  
Future Developments ◽  
Current State ◽  
Near Term ◽  
Over Time

Near-term iterative forecasting is a powerful tool for ecological decision support and has the potential to transform our understanding of ecological predictability. However, to this point, there has been no cross-ecosystem analysis of near-term ecological forecasts, making it difficult to synthesize diverse research efforts and prioritize future developments for this emerging field. In this study, we analyzed 178 near-term ecological forecasting papers to understand the development and current state of near-term ecological forecasting literature and compare forecast skill across ecosystems and variables. Our results indicate that near-term ecological forecasting is widespread and growing: forecasts have been produced for sites on all seven continents and the rate of forecast publication is increasing over time. As forecast production has accelerated, a number of best practices have been proposed and application of these best practices is increasing. In particular, data publication, forecast archiving, and workflow automation have all increased significantly over time. However, adoption of proposed best practices remains low overall: for example, despite the fact that uncertainty is often cited as an essential component of an ecological forecast, only 45% of papers included uncertainty in their forecast outputs. As the use of these proposed best practices increases, near-term ecological forecasting has the potential to make significant contributions to our understanding of predictability across scales and variables. In this study, we found that forecast skill decreased in predictable patterns over 1–7 day forecast horizons. Variables that were closely related (i.e., chlorophyll and phytoplankton) displayed very similar trends in predictability, while more distantly related variables (i.e., pollen and evapotranspiration) exhibited significantly different patterns. Increasing use of proposed best practices in ecological forecasting will allow us to examine the forecastability of additional variables and timescales in the future, providing a robust analysis of the fundamental predictability of ecological variables.

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