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Open Access
Article
Publication date: 23 January 2024

Rachael Hains-Wesson and Kaiying Ji

In this study, the authors explore students' and industry’s perceptions about the challenges and opportunities of participating in a large-scale, non-compulsory, individual…

Abstract

Purpose

In this study, the authors explore students' and industry’s perceptions about the challenges and opportunities of participating in a large-scale, non-compulsory, individual, in-person and unpaid business placement programme at an Australian university. The placement programme aims to support students' workplace transition by emphasising the development of key employability skills through reflective learning and linking theory to practice.

Design/methodology/approach

Utilising a case study methodology and integrating survey questionnaires, the authors collected both quantitative and qualitative data with large sample sizes.

Findings

The results highlight curriculum areas for improvement, emphasising tailored feedback to manage placement expectations and addressing employability skill strengths and weaknesses.

Practical implications

Recommendations include co-partnering with students to develop short, tailored and hot tip videos along with online learning modules, including the presentation of evidence-based statistics to inform students about post-programme employment prospects.

Originality/value

The study contributes to benchmarking good practices in non-compulsory, individual, in-person and unpaid placement pedagogy within the business education context.

Details

Journal of Work-Applied Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2205-2062

Keywords

Open Access
Article
Publication date: 10 June 2022

Ada Kwan, Rachel Sklar, Drew B. Cameron, Robert C. Schell, Stefano M. Bertozzi, Sandra I. McCoy, Brie Williams and David A. Sears

This study aims to characterize the June 2020 COVID-19 outbreak at San Quentin California State Prison and to describe what made San Quentin so vulnerable to uncontrolled…

958

Abstract

Purpose

This study aims to characterize the June 2020 COVID-19 outbreak at San Quentin California State Prison and to describe what made San Quentin so vulnerable to uncontrolled transmission.

Design/methodology/approach

Since its onset, the COVID-19 pandemic has exposed and exacerbated the profound health harms of carceral settings, such that nearly half of state prisons reported COVID-19 infection rates that were four or more times (and up to 15 times) the rate found in the state’s general population. Thus, addressing the public health crises and inequities of carceral settings during a respiratory pandemic requires analyzing the myriad factors shaping them. In this study, we reported observations and findings from environmental risk assessments during visits to San Quentin California State Prison. We complemented our assessments with analyses of administrative data.

Findings

For future respiratory pathogens that cannot be prevented with effective vaccines, this study argues that outbreaks will no doubt occur again without robust implementation of additional levels of preparedness – improved ventilation, air filtration, decarceration with emergency evacuation planning – alongside addressing the vulnerabilities of carceral settings themselves.

Originality/value

This study addresses two critical aspects that are insufficiently covered in the literature: how to prepare processes to safely implement emergency epidemic measures when needed, such as potential evacuation, and how to address unique challenges throughout an evolving pandemic for each carceral setting.

Details

International Journal of Prisoner Health, vol. 19 no. 3
Type: Research Article
ISSN: 1744-9200

Keywords

Content available
Article
Publication date: 18 May 2023

Adam Biggs, Greg Huffman, Joseph Hamilton, Ken Javes, Jacob Brookfield, Anthony Viggiani, John Costa and Rachel R. Markwald

Marksmanship data is a staple of military and law enforcement evaluations. This ubiquitous nature creates a critical need to use all relevant information and to convey outcomes in…

Abstract

Purpose

Marksmanship data is a staple of military and law enforcement evaluations. This ubiquitous nature creates a critical need to use all relevant information and to convey outcomes in a meaningful way for the end users. The purpose of this study is to demonstrate how simple simulation techniques can improve interpretations of marksmanship data.

Design/methodology/approach

This study uses three simulations to demonstrate the advantages of small arms combat modeling, including (1) the benefits of incorporating a Markov Chain into Monte Carlo shooting simulations; (2) how small arms combat modeling is superior to point-based evaluations; and (3) why continuous-time chains better capture performance than discrete-time chains.

Findings

The proposed method reduces ambiguity in low-accuracy scenarios while also incorporating a more holistic view of performance as outcomes simultaneously incorporate speed and accuracy rather than holding one constant.

Practical implications

This process determines the probability of winning an engagement against a given opponent while circumventing arbitrary discussions of speed and accuracy trade-offs. Someone wins 70% of combat engagements against a given opponent rather than scoring 15 more points. Moreover, risk exposure is quantified by determining the likely casualties suffered to achieve victory. This combination makes the practical consequences of human performance differences tangible to the end users. Taken together, this approach advances the operations research analyses of squad-level combat engagements.

Originality/value

For more than a century, marksmanship evaluations have used point-based systems to classify shooters. However, these scoring methods were developed for competitive integrity rather than lethality as points do not adequately capture combat capabilities. The proposed method thus represents a major shift in the marksmanship scoring paradigm.

Details

Journal of Defense Analytics and Logistics, vol. 7 no. 1
Type: Research Article
ISSN: 2399-6439

Keywords

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