It has been suggested that depressed individuals have difficulties decoding emotional facial expressions in others contributing to a negative cycle of interpersonal difficulties. Some studies have demonstrated global deficits in the processing of emotional facial expressions compared to non-depressed participants, whereas others have noted differences for specific emotions. Methodological issues, including the operationalization of accuracy and bias and the examination of a limited range of emotion and intensity, can partially explain the mixed findings. The aim of the current study was to examine differences in accuracy in the detection of emotional facial expressions in participants with MDD (currently depressed, partially remitted, and those with a lifetime history of MDD) and non-depressed comparisons. Methodological limitations of previous studies were addressed by: (a) using the unbiased hit rate (Wagner, 1993), which is a more precise measure of accuracy for specific emotion, (b) using a more precise measure of judgment bias, taking into account the overuse or underuse of specific emotion categories, (c) including the six basic emotions, and (d) incorporating expressions ranging from 20%-100% intensity. Of secondary interest was to determine whether transient mood state is predictive of accuracy scores regardless of diagnostic status. Thirty-seven depressed and 34 non-depressed participants recruited from the ROHCG Mood Disorders program and the University of Ottawa took part in this study. Clinical status was assessed using the Structured Clinical Interview for the DSM-IV (SCID-IV) and the Beck Depression Inventory-II (BDI-II). Participants also completed the Profile of Mood States-Bipolar (POMS-BI) form to assess mood state at the time of testing. The facial recognition task consisted of happiness, sadness, anger, fear, disgust, and surprise at 20%-100% intensity, presented for 500 ms. Participants pressed a computer key to identify the emotion that was presented. Results indicated that both groups of depressed participants were more accurate than non-depressed participants in detecting anger at 20% intensity. Depressed participants also showed a bias away from surprise. Group differences at high intensity were non-significant, however, participants with current depression and partial remission showed a bias towards anger at 50% intensity. Regression analyses were performed using the POMS-Agreeable Hostile (POMS-AH) and POMS-Elated Depressed (POMS-ED) scales to determine whether mood state was predictive of accuracy in the detection of anger and sadness. Regression models predicting accuracy were non-significant. Results of this study are considered in the context of cognitive and cognitive-interpersonal theories of MDD.

This thesis, written in conjunction for the School of Law and Graduate School of Philosophy offers a legal and theoretical exploration of gendered pseudonymous litigation. Pseudonymous litigation, most commonly the use of “Jane Doe" or "John Doe” seeks to provide anonymity for parties in litigation concerning sensitive matters. However, this traditional practice inserts bias into the legal process by indicating the gender of the parties. Not only does this allow for bias based on gender, but it can also allow for bias based on sexual orientation and can prevent non-binary and transgender individuals from being able to identify properly. This thesis explores these concerns and advocates for eliminating the use of gendered party names and pronouns in pseudonymous litigation.

Previous research has provided promising evidence for the effectiveness of video interventions to raise awareness of the gender bias that exists in science, technology, engineering, and math (STEM) fields. However, creating these beneficial video interventions can be costly and its possible that the success of these interventions may be hindered if a certain amount of resources are not invested into their creation (e.g., into high quality actors). Therefore, the current study expands on this research by investigating the use of personal testimonials of women’s experiences with gender bias in STEM as gender bias interventions. More specifically, I examined whether certain characteristics (e.g., genuineness) of the testimonial’s communicator would influence the relevant gender bias outcome (e.g., awareness of bias and sexism). I predicted that watching a woman genuinely talking about her experiences with bias, relative to a scripted re-telling of this story, would lead to better perceptions of the woman (e.g., more positive perceptions and perceptions of genuineness), greater feelings of empathy and connection with the woman, as well as less greater awareness of gender bias and less sexism from participants. To test this possibility, participants in the study were randomly assigned to interact with one of four story formats, a genuine telling of the woman’s experiences with bias, a scripted re-telling of these experiences, a written version of the story, or a unrelated control video. After interacting with the story participants then completed measures related to perceptions of the woman and gender bias. The findings of the study were limited, possibly due to a lack of power, but were encouraging as they were in the expected direction. The implications of the findings as well as future research ideas to expand and improve on these findings are discussed.

Emotional experiences are more likely to be remembered than more neutral, mundane ones. In young adults, negative information may be particularly memorable. Yet, an interesting change seems to happen in aging: As adults grow older, they may start remembering positive information more often than negative information. This positive memory bias in aging is commonly observed and is often explained in terms of changing time perspectives and motivation across the lifespan (i.e., Socioemotional Selectivity Theory; Carstensen, Isaacowitz, & Charles, 1999). However, few studies have considered the basic interactions between memory and emotion that could influence this positivity bias. In this thesis, I examine whether certain factors partially independent of aging (i.e., semantic relatedness and distinctiveness, Study 1; mood, Studies 2-4), might influence the presence and magnitude of the positivity bias in memory. In Study 1, I explore the cognitive mechanisms required to produce the positivity bias and apply what is learned in this paper to investigate, in Studies 2-4, whether differences in mood could explain why the positivity bias occurs. In all studies, memory is measured using immediate free recall of positive, negative, and neutral pictures. In Study 1, I manipulate item interrelatedness (i.e., the extent of relatedness among pictures of a same category) and relative distinctiveness (i.e., the processing of a picture category at the same time as or in isolation from the others) to show that older adults’ emotional memory can be entirely explained by these two factors. The distinctive processing of positive pictures relative to other pictures is necessary for producing a positivity bias in older adults, which completely disappears when the distinctive processing of positive pictures is removed. Therefore, in subsequent studies I encourage the distinctive processing of items to increase the likelihood of observing a positivity bias and its possible interaction with mood. In Study 2, I test whether differences in mood predict differences in emotional memory bias in young and older adults using a video mood induction technique validated in a separate pilot study. In Studies 3 and 4, I further test the effect of mood on the positivity bias beyond any age-specific factors, by examining young adults only. This serves to reduce the likelihood of confounds that might exist between age groups (i.e., related to neurocognitive changes or decline), in order to study the true effects of mood on the positivity bias. In Study 3, I use a written priming task to experimentally manipulate mood and time perspective in young adults. In Study 4, I compare differences in naturally occurring moods and emotional memory in two separate young adult samples: university students and non-students. The experimental mood manipulations have minimal influence on the presence of a negativity bias in young adults (Studies 2 and 3), and influence to a small extent the memory advantage of positive over neutral material in older adults (Study 2). Non-student young adults show a similar preferential memory for positive material that is different from what is observed in university students, but this is not easily attributed to differences in mood (Study 4). In light of these results, I argue that the positivity effect in aging memory reflects a temporary contextual advantage for positive information that is not permanent or irreversible. Rather, it seems to depend in varying degrees on the context of study (i.e., relatedness and distinctiveness), mood, and the young-adult reference group. This has implications for how future research defines and studies the positivity effect in aging.

Gender differences are frequently revealed on the popular TOSCA-2 measure of guilt- and shame-proneness. These gender differences could reflect biases in the eliciting conditions that participants evaluate and confounds between them. A new instrument, the Gender Relevant Test of Self-Conscious Affect (GR-TOSCA), was developed to eliminate these confounds, thereby introducing a gender-sensitive, and therefore more valid, measure of guilt and shame proneness. The psychometric integrity of the new instrument, hypotheses regarding condition-specific gender differences in the two emotions, and relationships of guilt- and shame-proneness scores to gender role endorsement were examined in a sample of undergraduate students (93 men and 109 women). Encouraging evidence was produced for the reliability and validity of the GR-TOSCA, but the hypothesized gender differences in guilt and shame proneness were not found. Several possibilities for these results are explored, including the possibility of biases in the research procedure.

No description available.

This study examined perceptions among non-racists, aversive racists, and blatant racists of differentially-performing African-American employees and the effects of the evaluation manipulation on future hiring decisions of an African-American applicant. Using a procedure for categorizing participants into one of these three racism groups, which utilized both implicit and explicit measures of racism, an internet-based sample (n = 221) rated the job performance of a European- or African-American incumbent law associate in a positive or mediocre performance condition and then provided performance ratings of the incumbent associate. Participants also evaluated a moderately-qualified African-American's hireability. Racism group, incumbent performance, and incumbent race were hypothesized to interact to differentially affect mediocre-performing African-American incumbent performance ratings and African-American applicant hireability and qualification ratings. The hypothesized three-way interactions were not significant. However, a significant two-way interaction of incumbent race X incumbent performance was found for incumbent performance ratings, F(1, 191) = 6.06, p = .015, ηp2 = .031, and African-American applicant hireability, F(1, 191) = 7.31, p = .007, ηp2 = .037. Hierarchical regression analyses probing the interactions showed that the positive-performing African-American incumbent's performance was rated significantly higher than the positive-performing European-American's performance, simple slope = .13, SE = .10, t = 2.10, p = .037. Participants also rated an African-American job applicant's hireability lower after viewing a mediocre-performing African-American incumbent, as compared to a mediocre-performing European-American incumbent, simple slope = -.18, SE = .14, t = -2.36, p = .019. These findings are consistent with the theoretical tenets of aversive racism. This study also explored the political ideologies of non-racists, aversive racists, and blatant racists. Using chi-square analysis, the political ideologies (conservative or liberal) of the three racist groups were significantly different, χ2 (2) = 43.03, p < .001. The majority of non-racists and aversive racists identified as liberal, whereas the majority of blatant racists identified as conservative. Although several key hypotheses were not supported, this study did provide further distinctions between aversive racists, blatant racists, and non-racists. Although differences were not found between the racism groups, the pattern of findings is suggestive of aversive racism. Furthermore, the finding that aversive racists were predominantly liberal supported previous findings concerning aversive racists' political ideologies.

Tracking systems are already encountered in everyday life in numerous applications, but many algorithms from the existing literature rely on assumptions that do not always hold in realistic scenarios, or can only be applied in niche circumstances. Therefor this thesis is motivated to develop new approaches that relax assumptions and restrictions, improve tracking performance, and are applicable in a broad range of scenarios. In the area of terrain-aided tracking this an algorithm is proposed to track targets using a Gaussian mixture measurement distribution to better represent multimodal distributions that can arise due to terrain conditions. This allowed effective use in a wider range of terrain conditions than existing approaches, which assume a unimodal Gaussian measurement distribution. Next, the problem of estimating and compensating for sensor biases is considered in the context of terrain-aided tracking. Existing approaches to bias estimation cannot be easily reconciled with the nonlinear converted measurement model applied in terrain-aided tracking. To address this, a novel efficient bias estimation algorithm is proposed that can be applied to a wide range of measurement models and operational scenarios, allowing for effective bias estimation and measurement compensation to be performed in situations that cannot be handled by existing algorithms. Finally, to address scenarios where converted measurement tracking is not possible or desired, the problem of sensor motion compensation when tracking in pixel coordinates is considered. Existing approaches compensate for sensor motion by transforming state estimates between frames, but are only able to achieve partial transformation of the state estimate and its covariance matrix. This thesis proposes a novel algorithm used to transform the full state estimate and its covariance matrix, improving tracking performance when tracking with a low frame rate and when tracking targets moving with a nearly coordinated turn motion model. Each of the proposed algorithms are evaluated in several simulated scenarios and compared against existing approaches and baselines to demonstrate their efficacy. / Thesis / Doctor of Philosophy (PhD)

An ongoing debate in society is about the existence of a wage gap between genders, and society’s alleged preference to hire a man over an equally qualified woman. This debate extends from the commercial employment world into the funding of research grants. Given data collected at North Dakota State University between 2012 and 2018 have women who have sought federal funding for their research experienced a gender bias? To investigate, a logistic regression model is fit to determine whether gender affects funding probability. Other characteristics such as the primary investigator’s college, requested amount, and the research team’s make up of tenured and Caucasian members is also investigated. It was found that there is not a gender bias towards faculty at NDSU. Naturally, there was a bias towards researchers from different colleges and towards proposals requesting less funding. Surprisingly, a bias towards higher-proportion Caucasian research projects was found.

Structural equation modeling was utilized to test a hypothesized model for the effects of negative biases, thought suppression, experiential avoidance, and mindfulness on pathological anxiety. Self-report scales were used to measure each construct. Confirmatory factor analyses were used to test the factor structure of each scale. Identified factors were disparate from those in previous research on some scales, so items from scales were pooled to create scales for each construct. Alternate models were tested. No models showed adequate fit. Significant paths between most constructs partially supported our theory. Surprisingly, thought suppression did not predict anxiety. This finding is important because previous literature cites parallels between thought suppression and experiential avoidance to explain the role of experiential avoidance in anxiety. Additionally, the effects of mindfulness on anxiety were mediated by experiential avoidance and negativity bias, providing a possible explanation for the efficacy of mindfulness based treatments for anxiety.