Like trainer, like bot? Inheritance of bias in algorithmic content moderation

The internet has become a central medium through which `networked publics' express their opinions and engage in debate. Offensive comments and personal attacks can inhibit participation in these spaces. Automated content moderation aims to overcome this problem using machine learning classifiers trained on large corpora of texts manually annotated for offence. While such systems could help encourage more civil debate, they must navigate inherently normatively contestable boundaries, and are subject to the idiosyncratic norms of the human raters who provide the training data. An important objective for platforms implementing such measures might be to ensure that they are not unduly biased towards or against particular norms of offence. This paper provides some exploratory methods by which the normative biases of algorithmic content moderation systems can be measured, by way of a case study using an existing dataset of comments labelled for offence. We train classifiers on comments labelled by different demographic subsets (men and women) to understand how differences in conceptions of offence between these groups might affect the performance of the resulting models on various test sets. We conclude by discussing some of the ethical choices facing the implementers of algorithmic moderation systems, given various desired levels of diversity of viewpoints amongst discussion participants.Comment: 12 pages, 3 figures, 9th International Conference on Social Informatics (SocInfo 2017), Oxford, UK, 13--15 September 2017 (forthcoming in Springer Lecture Notes in Computer Science

Health services research: building capacity to meet the needs of the healthcare system

Health services researchers have an important role to play in helping health care systems around the world provide high quality, affordable services. However, gaps between the best evidence and current practice suggest that researchers need to work in new ways. The production of research that meets the needs and priorities of the health system requires researchers to work in partnership with decision-makers to conduct research and then mobilize the findings. To do this effectively, researchers require a new set of skills that are not conventionally taught as part of doctoral research programmes. In addition to wider contextual changes, researchers need to understand better the needs of decision-makers, for example through short placements in health system decision-making settings. Second, researchers need to learn to accommodate those needs throughout the research process, including identifying research needs; conducting research collaboratively with decision-makers and producing effective research products

Colored Resonant Signals at the LHC: Largest Rate and Simplest Topology

We study the colored resonance production at the LHC in a most general approach. We classify the possible colored resonances based on group theory decomposition, and construct their effective interactions with light partons. The production cross section from annihilation of valence quarks or gluons may be on the order of 400 - 1000 pb at LHC energies for a mass of 1 TeV with nominal couplings, leading to the largest production rates for new physics at the TeV scale, and simplest event topology with dijet final states. We apply the new dijet data from the LHC experiments to put bounds on various possible colored resonant states. The current bounds range from 0.9 to 2.7 TeV. The formulation is readily applicable for future searches including other decay modes.Comment: 29 pages, 9 figures. References updated and additional K-factors include

Atmospheric emissions from the deepwater Horizon spill constrain air-water partitioning, hydrocarbon fate, and leak rate

The fate of deepwater releases of gas and oil mixtures is initially determined by solubility and volatility of individual hydrocarbon species; these attributes determine partitioning between air and water. Quantifying this partitioning is necessary to constrain simulations of gas and oil transport, to predict marine bioavailability of different fractions of the gas-oil mixture, and to develop a comprehensive picture of the fate of leaked hydrocarbons in the marine environment. Analysis of airborne atmospheric data shows massive amounts (∼258,000 kg/day) of hydrocarbons evaporating promptly from the Deepwater Horizon spill; these data collected during two research flights constrain air-water partitioning, thus bioavailability and fate, of the leaked fluid. This analysis quantifies the fraction of surfacing hydrocarbons that dissolves in the water column (∼33% by mass), the fraction that does not dissolve, and the fraction that evaporates promptly after surfacing (∼14% by mass). We do not quantify the leaked fraction lacking a surface expression; therefore, calculation of atmospheric mass fluxes provides a lower limit to the total hydrocarbon leak rate of 32,600 to 47,700 barrels of fluid per day, depending on reservoir fluid composition information. This study demonstrates a new approach for rapid-response airborne assessment of future oil spills. Copyright 2011 by the American Geophysical Union

Fertility Desire and Intention of People Living with HIV/AIDS in Tanzania: A call for Restructuring Care and Treatment Services.

Scaling up of antiretroviral therapy (ART) is currently underway in sub-Saharan Africa including, Tanzania, increasing survival of people living with HIV/AIDS (PLWHA). Programmes pay little attention to PLWHA's reproductive health needs. Information on fertility desire and intention would assist in the integration of sexual and reproductive health in routine care and treatment clinics. A cross-sectional study of all PLWHA aged 15--49 residing in Kahe ward in rural Kilimanjaro Tanzania was conducted. Participants were recruited from the community and a local counselling centre located in the ward. Data on socio-demographic, medical and reproductive characteristics were collected through face-to-face interviews. Data were entered and analysed using STATA statistical software. A total of 410 PLWHA with a mean age of 34.2 and constituting 264 (64.4%) females participated. Fifty-one per cent reported to be married/cohabiting, 73.9% lived with their partners and 60.5% were sexually active. The rate of unprotected sex was 69.0% with 12.5% of women reporting to be pregnant at the time of the survey. Further biological children were desired by 37.1% of the participants and lifetime fertility intention was 2.4 children. Increased fertility desire was associated with living and having sex with a partner, HIV disclosure, good perceived health status and CD4 count >=200 cells for both sexes. Reduced desire was associated with havingmore than 2 children among females, divorce or separation, and having a child with the current partner among both males and females. Fertility desire and intention of PLWHA was substantially high though lower than that of the general population in Tanzania. Practice of unprotected sexual intercourse with higher pregnancy rate was observed. Fertility desire was determined by individual perceived health and socio-family related factors. With increasing ART coverage and subsequent improved quality of life of PLWHA, these findings underscore the importance of integrating reproductive health services in the routine care and treatment of HIV/AIDS worldwide. The results also highlight a group of PLWHA with potentially high desire for children who need to be targeted during care

Computer-vision based method for quantifying rising from chair in Parkinson's disease patients

BACKGROUND: The ability to arise from a sitting to a standing position is often impaired in Parkinson's disease (PD). This impairment is associated with an increased risk of falling, and higher risk of dementia. We propose a novel approach to estimate Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS) ratings for “item 3.9” (arising from chair) using a computer vision-based method, whereby we use clinically informed reasoning to engineer a small number of informative features from high dimensional markerless pose estimation data. METHODS: We analysed 447 videos collected via the KELVIN-PD™ platform, recorded in clinical settings at multiple sites, using commercially available mobile smart devices. Each video showed an examination for item 3.9 of the MDS-UPDRS and had an associated severity rating from a trained clinician on the 5-point scale (0, 1, 2, 3 or 4). The deep learning library OpenPose was used to extract pose estimation key points from each frame of the videos, resulting in time-series signals for each key point. From these signals, features were extracted which capture relevant characteristics of the movement; velocity variation, smoothness, whether the patient used their hands to push themselves up, how stooped the patient was while sitting and how upright the patient was when fully standing. These features were used to train an ordinal classification system (with one class for each of the possible ratings on the UPDRS), based on a series of random forest classifiers. RESULTS: The UPDRS ratings estimated by this system, using leave-one-out cross validation, corresponded exactly to the ratings made by clinicians in 79% of videos, and were within one of those made by clinicians in 100% of cases. The system was able to distinguish normal from Parkinsonian movement with a sensitivity of 62.8% and a specificity of 90.3%. Analysis of misclassified examples highlighted the potential of the system to detect potentially mislabelled data. CONCLUSION: We show that our computer-vision based method can accurately quantify PD patients’ ability to perform the arising from chair action. As far as we are aware this is the first study estimating scores for item 3.9 of the MDS-UPDRS from singular monocular video. This approach can help prevent human error by identifying unusual clinician ratings, and provides promise for such a system being used routinely for clinical assessments, either locally or remotely, with potential for use as stratification and outcome measures in clinical trials

Does owning a pet protect older people against loneliness?

This article has been made available through the Brunel Open Access Publishing Fund.Pet ownership is thought to make a positive contribution to health, health behaviours and the general well-being of older people. More specifically pet ownership is often proposed as a solution to the problem of loneliness in later life and specific 'pet based' interventions have been developed to combat loneliness. However the evidence to support this relationship is slim and it is assumed that pet ownership is a protection against loneliness rather than a response to loneliness. The aim of this paper is to examine the association between pet ownership and loneliness by exploring if pet ownership is a response to, or protection against, loneliness using Waves 0-5 from the English Longitudinal Study of Ageing (ELSA)

Prevalence and Determinants of Obesity among Primary School Children in Dar es Salaam, Tanzania.

Childhood obesity has increased dramatically and has become a public health concern worldwide. Childhood obesity is likely to persist through adulthood and may lead to early onset of NCDs. However, there is paucity of data on obesity among primary school children in Tanzania. This study assessed the prevalence and determinants of obesity among primary school children in Dar es Salaam. A cross sectional study was conducted among school age children in randomly selected schools in Dar es Salaam. Anthropometric and blood pressure measurements were taken using standard procedures. Body Mass Index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m2). Child obesity was defined as BMI at or above 95th percentile for age and sex. Socio-demographic characteristics of children were determined using a structured questionnaire. Logistic regression was used to determine association between independent variables with obesity among primary school children in Dar es Salaam. A total of 446 children were included in the analysis. The mean age of the participants was 11.1±2.0 years and 53.1% were girls. The mean BMI, SBP and DBP were 16.6±4.0 kg/m2, 103.9±10.3mmHg and 65.6±8.2mmHg respectively. The overall prevalence of child obesity was 5.2% and was higher among girls (6.3%) compared to boys (3.8%). Obese children had significantly higher mean values for age (p=0.042), systolic and diastolic blood pressures (all p<0.001). Most obese children were from households with fewer children (p=0.019) and residing in urban areas (p=0.002). Controlling for other variables, age above 10 years (AOR=3.3, 95% CI=1.5-7.2), female sex (AOR=2.6, 95% CI=1.4-4.9), urban residence (AOR=2.5, 95% CI=1.2-5.3) and having money to spend at school (AOR=2.6, 95% CI=1.4-4.8) were significantly associated with child obesity. The prevalence of childhood obesity in this population was found to be low. However, children from urban schools and girls were proportionately more obese compared to their counterparts. Primary preventive measures for childhood obesity should start early in childhood and address socioeconomic factors of parents contributing to childhood obesity