Not one of us is without bias : identifying and challenging racism and homophobia

This article reviews a teaching process that aimed to prepare final year social work students for critical practice with diverse and marginalized populations. Alongside lecture input, in small group discussions and in the two sequenced written assignments students were encouraged to personalize questions of bias and stigma by recalling both their experiences of being “other-ed” as well as their participation in practices that “other-ed”, such as racist and homophobic imaging and acting. Feedback to the unit’s first iteration in 2004 was generally positive yet a significant minority of students were clearly dissatisfied. Whilst retaining the same formal content in 2005, greater attention was devoted to generating a supportive group process and a positive environment for “negative” self-disclosure. This milieu acted to contain and normalize the students’ struggle with internalized stereotypes, a stage associated with their greater preparedness to identify and challenge their own personal, cultural and ideological locations. Within the context of the unit remaining explicit about its value stance, by adopting an approach to the teaching / learning process that neither collided nor colluded, as teachers we believe the 2005 revision better achieved the units aims. First, the unit received broader positive appraisal from students and, second, it appeared that the unit more firmly promoted the prospects for students carrying forward a capacity for critical self review post graduation.

Improving reliability of unbalanced text mining by reducing performance bias

Class imbalance in textual data is one important factor that affects the reliability of text mining. For imbalanced textual data, conventional classifiers tend to have a strong performance bias, which results in high accuracy rate on the majority class but very low rate on the minorities. An extreme strategy for unbalanced learning is to discard the majority instances and apply one-class classification to the minority class. However, this could easily cause another type of bias, which increases the accuracy rate on minorities by sacrificing the majorities. This chapter aims to investigate approaches that reduce these two types of performance bias and improve the reliability of discovered classification rules. Experimental results show that the inexact field learning method and parameter optimized one class classifiers achieve more balanced performance than the standard approaches.

Privacy threat analysis of social network data

Social network data has been increasingly made publicly available and analyzed in a wide spectrum of application domains. The practice of publishing social network data has brought privacy concerns to the front. Serious concerns on privacy protection in social networks have been raised in recent years. Realization of the promise of social networks data requires addressing these concerns. This paper considers the privacy disclosure in social network data publishing. In this paper, we present a systematic analysis of the various risks to privacy in publishing of social network data. We identify various attacks that can be used to reveal private information from social network data. This information is useful for developing practical countermeasures against the privacy attacks.

Unis accused of 'elite bias' in enrolments

Australia’s elite universities are biased against taking disadvantaged students for fear it will lower their prestigious image, an Adelaide academic says.

Anger at schools' Christian 'bias'

Buddhist community leader Dr Sue Smith has complained of the ''Christian bias'' in religious education in Victoria, saying if her group had access to government funding, they too could expand to hundreds of schools.

Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling

Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, ‘hidden’ trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

Estimating non-response bias in a web-based survey of technology acceptance : a case study of unit guide information systems

Surveys are mostly challenged by response rates. Among the various types of survey research, web-based (internet-based/electronic/online) surveys are commonly used for data collection for a geographically diverse population. In surveys with high/low response rates, non-response bias can be a major concern. While it is not always possible to measure the actual bias due to non-response there are different approaches and techniques that help to identify reasons of non-response bias. The aims of this paper are twofold. (1) To provide an appropriate, interesting and important non-response bias case study for future web-based surveys that will provide guidance to other Information Systems researchers. The case-study concerns an online-survey to evaluate a technology acceptance model for Unit Guide Information systems (UGIS). (2) To discuss how nonresponse bias in a web-based technology acceptance study of an information system (UGIS in this case) can be contained and managed.

The relationship between attachment style, anxiety sensitivity and interpretive bias among adolescent nonclinical panickers

Elevated anxiety sensitivity and the tendency to catastrophically misinterpret ambiguous bodily sensations has been demonstrated in people who experience nonclinical levels of panic (Richards, Austin, & Alvarenga, 2001), and anxiety sensitivity has been shown to be associated with insecure attachment in adolescents and young adults (Weems, Berman, Silverman, and Saavedra, 2001). This study investigated the relationship between attachment style, anxiety sensitivity and catastrophic misinterpretation among 11 nonclinical panickers and 58 nonanxious controls aged 18 to 19 years. Participants completed the Brief Bodily Sensations Interpretation Questionnaire (BBSIQ), Anxiety Sensitivity Index (ASI) and an attachment questionnaire. The hypothesis that insecurely attached individuals would demonstrate greater catastrophic misinterpretation and higher anxiety sensitivity than securely attached individuals was not supported; however, nonclinical panickers gave more anxiety-related interpretations of ambiguous internal stimuli than nonanxious controls. Results do not support the notion that attachment style is related to anxiety sensitivity or catastrophic misinterpretation (regardless of panic experience). Results do, however, support the notion that anxiety-related misinterpretation of ambiguous somatic sensations precedes the onset of panic disorder.

Anxiety versus fundamental emotions as predictors of perceived functionality of pre-competitive emotional states, threat, and challenge in individual sports

The objectives of this study were to examine the contribution of anxiety and fundamental emotions to perceived emotion functionality and evaluate the informational value of anxiety measures used in sport versus measures of fundamental emotions in terms of appraisal. A battery of questionnaires comprising the somatic and cognitive subscale of the Competitive State Anxiety Inventory-2 (CSAI-2), the State Anxiety Inventory, the Differential Emotions Scale–IV, a perceived functionality of emotions single item, and two items assessing challenge and threat appraisals was administered to 202 athletes competing in individual sports in the United Kingdom. They were tested on recalled pre-competitive emotions experienced before their best and worst competition ever and momentary emotions experienced one hour before an actual competition. In general, measures of fundamental emotions with clear approach or avoidance action tendencies were better predictors of emotion functionality than anxiety measures. Results also suggested that the CSAI-2 does not convey clear information about an athlete’s appraisal of a competition. Measures of negative and positive fundamental emotions with clear action tendencies were better indicators of athletes’ appraisal patterns. It was concluded that assessment of athletes’ emotional state should not be exclusively based on anxiety measures but should encompass or be replaced with measures of emotions conveying unambiguous information about the athlete-competition relationship.