scholarly journals “Lock This Whore Up”: Legal Violence and Flows of Information Precipitating Personal Violence against People Criminalised for HIV-Related Crimes in Canada

2019 ◽  
Vol 10 (1) ◽  
pp. 132-147 ◽  
Author(s):  
Alexander MCCLELLAND
Keyword(s):  
Big Data ◽  
Perceived Risk ◽  
Hiv Positive ◽  
Sex Partners ◽  
Daily Lives ◽  
Public Control ◽  
Legal Violence ◽  
Data Surveillance ◽  
Flow Of Information ◽  
Personal Violence

This article examines the convergence of myriad forms of information on people who come to be targets of state and public control due to the perceived risk they present through having been alleged to have not disclosed their HIV-positive status to sex partners. Attending to the material, violent impacts of criminalisation – violence, both legal and extralegal – this article outlines how punishment is enhanced and amplified through the flow of information. Focusing on the material impacts of flows of information about the daily lives of people who face criminalisation moves analysis beyond solely a theoretical object of inquiry and helps to frame an understand that the effects of big data operate not just “within” big data surveillance, but also “beyond” big data surveillance.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Australian gay and bisexual men’s online preferences about sex with HIV-positive partners

Sexual Health ◽  
2017 ◽  
Vol 14 (3) ◽  
pp. 221 ◽  
Author(s):  
Garrett Prestage ◽  
Benjamin Bavinton ◽  
Denton Callander ◽  
Steven P. Philpot ◽  
Iryna Zablotska ◽  
...  
Keyword(s):  
Safer Sex ◽  
Gay And Bisexual Men ◽  
Hiv Positive ◽  
Bisexual Men ◽  
Sex Partners ◽  
Hiv Status ◽  
Capital Cities ◽  
Gay Community ◽  
And Bisexual ◽  
Hiv Positive Men

Background Among gay and bisexual men (GBM), ‘serosorting’ is common and involves restricting sex, or at least condomless sex, to partners of the same HIV status. The prevalence of men conveying their serosorting preferences regarding partners they meet online remains unclear. Methods: This study reviewed 57 178 Australian online profiles obtained directly from a popular gay website. Logistic regression was used to identify factors associated with preferences for meeting HIV-positive partners. Results: Men could indicate their preferences from a list of 22 types of partners; 4358 profiles (7.6%) indicated an interest in meeting HIV-positive men. There were 1959 profiles (3.4%) listing a preference for 21 of the 22 types of men, including 1498 men (2.6%) that specifically excluded HIV-positive men. Men who specifically excluded HIV-positive men on their profiles were younger (mean age 34.7 years), less likely to identify as gay (25.6%) and more likely to always prefer ‘safer sex’ (55.3%) than those who specifically included them (mean age 39.6 years; 62.8% gay-identified; 30.9% preferred safer sex; P < 0.001). Men who specifically excluded HIV-positive partners on their profiles were also more likely to live outside major capital cities (P < 0.001). Conclusions: Being younger, living outside major cities, not identifying as gay, always preferring safer sex and either Caucasian or Asian background were associated with excluding HIV-positive men as potential sex partners. These factors may reflect lower social and community engagement with the gay community. The disinclination to include HIV-positive men as potential sex partners may be due to fear of infection, stigma or poor information about HIV.

scholarly journals Big Data Surveillance

2021 ◽  
Vol 4 (2) ◽  
pp. 95-98
Author(s):  
Valerie Steeves
Keyword(s):  
Big Data ◽  
Young People ◽  
Question And Answer ◽  
Data Surveillance

On October 21, 2021, Dr. Valerie Steeves presented Big Data Surveillance: Privacy and Trust Implications at the October 2021 CASIS Digital Roundtable event. This presentation was followed by a question and answer period, where CASIS Executives and attendees were given the opportunity to discuss the presentation with Dr. Steeves. The discussion topics included building an understanding of data surveillance for young people and safeguarding their privacy through building trusting relations.

scholarly journals Retrospective review of tertiary and neurosyphilis cases in Alberta, 1973–2017

BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e025995 ◽  
Author(s):  
Takaaki Landry ◽  
Petra Smyczek ◽  
Ryan Cooper ◽  
Jennifer Gratrix ◽  
Lindsay Bertholet ◽  
...  
Keyword(s):  
Retrospective Review ◽  
Hiv Positive ◽  
Ocular Involvement ◽  
Clinical Parameters ◽  
Sex Partners ◽  
Hiv Status ◽  
Same Sex ◽  
Notification Rate ◽  
Tertiary Syphilis ◽  
Common Manifestation

ObjectivesTo review the notification rate and characteristics of tertiary and neurosyphilis cases in Alberta, Canada in the postantibiotic era.MethodsA retrospective review of all neurosyphilis and tertiary syphilis cases reported in Alberta from 1973 to March 2017 was undertaken and cases classified into early neurosyphilis, late neurosyphilis and cardiovascular (CV) syphilis. Variables collected included demographics, sexual partners, HIV status, clinical parameters, symptoms and treatment and distributions were compared between early versus late neurosyphilis and asymptomatic versus symptomatic cases (stratified by early versus late stage). Data were analysed using IBM SPSS Statistics V.19.0.Results254 cases were identified; 251 were neurosyphilis and 3 were CV. No cases of gummatous syphilis were reported. Early neurosyphilis accounted for 52.4% (n=133) and 46.1% (n=117) were late neurosyphilis cases; one (0.4%) case with unknown duration. Three outbreaks of infectious syphilis were identified during the study period and a concurrent rise in both early and late neurosyphilis was observed during the outbreak periods. The most common manifestation of symptomatic neurosyphilis was ocular involvement which was more likely in early neurosyphilis. Relative to late neurosyphilis cases, early neurosyphilis cases were more likely to be younger, Caucasian, born in Canada, HIV positive and reporting same sex partners.ConclusionsOur review of tertiary and neurosyphilis cases found that early and late neurosyphilis cases continue to occur in the context of cycling syphilis outbreaks. CV syphilis cases were extremely rare. Ongoing identification of new cases of syphilis and clinical evaluation of cases for complications continues to be important in the context of global resurgence of syphilis.

scholarly journals High willingness to use novel HIV and bacterial sexually transmitted infection partner notification, testing, and treatment strategies among gay and bisexual men

2019 ◽  
Vol 96 (3) ◽  
pp. 173-176 ◽  
Author(s):  
Steven A John ◽  
Tyrel J Starks ◽  
H Jonathon Rendina ◽  
Jeffrey T Parsons ◽  
Christian Grov
Keyword(s):  
Perceived Risk ◽  
Partner Notification ◽  
Treatment Strategies ◽  
Gay And Bisexual Men ◽  
Casual Partner ◽  
Bisexual Men ◽  
Sex Partners ◽  
Anal Sex ◽  
Condomless Anal Sex ◽  
And Bisexual

ObjectivesWe sought to determine willingness of gay and bisexual men (GBM) to give HIV self-testing (HIVST) kits with patient-delivered partner therapy (PDPT) and engage in geosocial sexual networking (GSN) app-based partner notification.MethodsA nationwide sample of GBM who self-tested HIV negative (n=786) were asked about their willingness to give recent sex partners (main and casual) PDPT with an HIVST kit (PDPT+HIVST) after hypothetical bacterial STI (BSTI) diagnosis. Men were also asked about their willingness to notify sexual partners met on GSN apps using an anonymous app function after BSTI diagnosis. We examined associations of relationship status and condomless anal sex with casual partners, recent BSTI diagnosis and perceived risk of HIV on PDPT+HIVST and anonymous app-based partner notification willingness (dichotomised) using binary logistic regressions, adjusting for age, race/ethnicity, education and US region. From the partner’s perspective after receiving an app-based referral, frequency measures were used to report intentions for obtaining subsequent HIV/BSTI counselling and testing, engaging in HIVST if provided a free voucher, and obtaining BSTI treatment from a pharmacy with prescription voucher.ResultsMost (90.1%) were willing to give PDPT+HIVST to recent sex partners after STI diagnosis, and nearly all (96.4%) were willing to notify sex partners met online using an anonymous function within GSN apps. Regardless of casual partner condomless anal sex engagement, partnered GBM had higher odds of reporting willingness to give PDPT+HIVST compared with single men who recently engaged in condomless anal sex with a casual partner. If anonymously notified via an app, 92.5% reported they would likely obtain counselling and testing, 92.8% would engage in HIVST if provided a free voucher, and 93.4% would obtain treatment from a pharmacy with prescription voucher.ConclusionsGBM generally found novel partner notification, testing, and treatment strategies acceptable, indicating the need for feasibility and cost-effectiveness evaluations.

scholarly journals Big Data as a Source for Official Statistics

2015 ◽  
Vol 31 (2) ◽  
pp. 249-262 ◽  
Author(s):  
Piet J.H. Daas ◽  
Marco J. Puts ◽  
Bart Buelens ◽  
Paul A.M. van den Hurk
Keyword(s):  
Big Data ◽  
High Frequency ◽  
Electronic Devices ◽  
Point Of View ◽  
Data Sources ◽  
The Internet ◽  
Official Statistics ◽  
Daily Lives ◽  
Media Messages ◽  
Loop Detection

Abstract More and more data are being produced by an increasing number of electronic devices physically surrounding us and on the internet. The large amount of data and the high frequency at which they are produced have resulted in the introduction of the term ‘Big Data’. Because these data reflect many different aspects of our daily lives and because of their abundance and availability, Big Data sources are very interesting from an official statistics point of view. This article discusses the exploration of both opportunities and challenges for official statistics associated with the application of Big Data. Experiences gained with analyses of large amounts of Dutch traffic loop detection records and Dutch social media messages are described to illustrate the topics characteristic of the statistical analysis and use of Big Data.

Predictable policing: New technology, old bias, and future resistance in big data surveillance

2020 ◽  
Vol 26 (5-6) ◽  
pp. 1108-1124
Author(s):  
Xerxes Minocher ◽  
Caelyn Randall
Keyword(s):  
Big Data ◽  
Science And Technology Studies ◽  
New Technology ◽  
The United States ◽  
Surveillance Network ◽  
Predictive Policing ◽  
Sociotechnical System ◽  
Power And Control ◽  
Data Surveillance ◽  
And Control

Within this article, we explore the rise of predictive policing in the United States as a form of big data surveillance. Bringing together literature from communication, criminology, and science and technology studies, we use a case study of Milwaukee, Wisconsin, USA to outline that predictive policing, rather than being a novel development, is in fact part of a much larger, historical network of power and control. By examining the mechanics of these policing practices: the data inputs, behavioral outputs, as well as the key controllers of these systems, and the individuals who influenced their adoption, we show that predictive policing as a form of big data surveillance is a sociotechnical system that is wholly human-constructed, biases and all. Identifying these elements of the surveillance network then allows us to turn our attention to the resistive practices of communities who historically and presently live under surveillance – pointing to the types of actions and imaginaries required to combat the myth and allure that swirls around the rhetoric of big data surveillance today.

scholarly journals ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation

2020 ◽  
Vol 12 (14) ◽  
pp. 5605
Author(s):  
Yi-Zeng Hsieh ◽  
Shih-Syun Lin ◽  
Yu-Cin Luo ◽  
Yu-Lin Jeng ◽  
Shih-Wei Tan ◽  
...  
Keyword(s):  
Big Data ◽  
School Administrators ◽  
Rapid Development ◽  
Science And Technology ◽  
Recognition System ◽  
Learning Effectiveness ◽  
Daily Lives ◽  
Academic Difficulties ◽  
Science And Technology Education ◽  
Training Professional

Under the vigorous development of global anticipatory computing in recent years, there have been numerous applications of artificial intelligence (AI) in people’s daily lives. Learning analytics of big data can assist students, teachers, and school administrators to gain new knowledge and estimate learning information; in turn, the enhanced education contributes to the rapid development of science and technology. Education is sustainable life learning, as well as the most important promoter of science and technology worldwide. In recent years, a large number of anticipatory computing applications based on AI have promoted the training professional AI talent. As a result, this study aims to design a set of interactive robot-assisted teaching for classroom setting to help students overcoming academic difficulties. Teachers, students, and robots in the classroom can interact with each other through the ARCS motivation model in programming. The proposed method can help students to develop the motivation, relevance, and confidence in learning, thus enhancing their learning effectiveness. The robot, like a teaching assistant, can help students solving problems in the classroom by answering questions and evaluating students’ answers in natural and responsive interactions. The natural interactive responses of the robot are achieved through the use of a database of emotional big data (Google facial expression comparison dataset). The robot is loaded with an emotion recognition system to assess the moods of the students through their expressions and sounds, and then offer corresponding emotional responses. The robot is able to communicate naturally with the students, thereby attracting their attention, triggering their learning motivation, and improving their learning effectiveness.

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