Applied zooarchaeology provides baselines which can be used in modern conservation biology to better understand how faunal communities have changed over time. This goal can only be accomplished, however, by first accounting for the multiple biases present within the archaeological record, and how they may affect sample representativeness. Taxonomic analysis was conducted on freshwater mussel shell from the late prehistoric (ca. A.D. 700 - 1200) Kinlock site, Sunflower County, Mississippi. Species-area curves and biodiversity indices demonstrate that random sampling of surface clusters of shell, up to about 4,000 valves, provides an adequate picture of the overall surface assemblage. Comparison of surface and subsurface contexts shows a highly significant difference in species numbers and proportions, indicating a need for multi-context sampling when dealing with archaeological shell deposits.

Alcohol consumption is prevalent on college campuses. There are a number of theories that seek to explain the link between alcohol use and mood. The affective-processing model posits that negative affect may interact with subconscious cognitive factors, such as attention bias (AB), to promote drug-seeking behavior. In contrast, the incentive-sensitization model suggests positive mood may drive drug seeking behavior, and this drive may be moderated by cognitive factors (e.g., AB). The current study hypothesized that both positive and negative mood would be associated with drug craving in the moment. It was further hypothesized that AB would moderate mood-craving associations. Participants (n = 69) from a Midwestern University carried a mobile device for 15 days and provided ratings of momentary mood (positive mood, anxiety, anger, and sadness), craving, and attention bias. Across assessments, all four moods were positively associated with momentary craving (p < .05). There were significant interactions of Anxiety x AB, Anger x AB, and Positive Mood x AB; all of which varied by gender. For men, Anxiety (B = .15, p = .004) and Positive Mood (B = .22, p < .001) were more robustly associated with momentary craving when their AB was +1SD above their own mean. For women, Anger (B = .14, p = .001) was more robustly associated with momentary craving when their AB was +1SD above their own mean. These results indicate differential effects of AB on mood by gender. Theoretical models of mood x cognition interactions may have more nuanced effects based on one's gender. This suggests that different forms of mood may trigger drug seeking behavior for men and women, offering important gender differences in relapse risk.

Soil moisture is an essential climate variable and provides critical state information for hydrological applications. The state of soil moisture influences the exchange of water and energy between the earth surface and the atmosphere, partitions infiltration and runoff, can limit the net primary productivity of a region and govern the dynamics of geochemical processes. Satellite observations can be used to provide information about this important variable but are often available at a scale that is far greater than most hydrological processes. The scope of the research presented in this dissertation was to identify practical methods to facilitate the use of coarse scale satellite soil moisture information in higher resolution hydrological and land-surface modelling applications. Research was primarily conducted in the Hamilton-Halton watershed of Southern Ontario, Canada, although other watersheds and datasets were periodically used in some chapters. A comprehensive review was conducted on the use of high resolution soil moisture information for hydrological applications, and data assimilation was identified as the most common method for integrating soil moisture information into a hydrological model. It was also identified that most watersheds displayed the property of temporal persistence and that root-zone soil moisture was of greater importance than surface soil moisture (Appendix B). In light of this information, the focus of this research was the downscaling of soil moisture and brightness temperature (TB) observations from the Soil Moisture and Ocean Salinity (SMOS) passive microwave satellite. Satellite observations are sensitive to surface soil moisture, while rootzone soil moisture provides the greatest benefit to hydrological and land surface applications. To overcome this discrepancy, artificial neural networks (ANN) were evaluated as a method to estimate rootzone soil moisture from surface observations that accounted for the known non-linearities of soil moisture processes. The ANN model was trained with a numerical soil moisture physics model and validated using in situ observations from the McMaster Mesonet and USDA SCAN sites. The ANN was capable of accurately depicting the rootzone soil moisture based on its training data at multiple sites, but was limited when the temporal distribution of soil moisture at a particular site was considerably different than the training data. Therefore, with the appropriate training data, ANNs are a viable method for predicting rootzone soil moisture from surface observations such as those available from satellites. To provide high resolution soil moisture information from coarse resolution satellite data, bias correction was proposed and evaluated as a downscaling method for both soil moisture and TB. Using in situ data from two well instrumented USDA watersheds and a hydrological land-surface scheme (HLSS), it was found that temporal evolution of both soil moisture and TB at fine scale (~1 km) could be well characterized by the temporal evolution of the coarse scale (~20 km) soil moisture and TB. The fine scale spatial distribution of soil moisture could be predicted with a high degree of skill by correcting the bias between the coarse and fine scale soil moisture/TB. In studying the correction of biases, it was found that naïve application of bias correction methods could result in the introduction of multiplicative biases in the bias corrected dataset. The theoretical implications of this for a data assimilation system were discussed although not yet evaluated. A bootstrap resampling approach was evaluated as a solution to this problem and it was found that resampled data could result in a robust bias correction that eliminated additive bias in most instances while limiting the induction of multiplicative bias. This new method was found to significantly outperform the standard bias correction techniques. / Thesis / Doctor of Philosophy (PhD) / Soil moisture is an important hydrological variable. The state of soil moisture controls the partition between the runoff and infiltration as well as the exchange of heat from the surface to the atmosphere. Therefore, an accurate depiction of the state of soil moisture is important for producing accurate flood and drought forecasts, numerical weather prediction and agricultural forecasts. The state of soil moisture can be observed from space using microwave remote sensing measurements. However, the resolution of most passive microwave observations, such as those from the European Space Agency Soil Moisture and Ocean Salinity (SMOS) satellite are at a resolution of approximately 40 km which is far more coarse than the approximately 1 km resolution of most hydrological processes. The work in this thesis presented bias correction methods as a mean to match the spatial scale of the satellite observations to high resolution hydrological and land surface models. These data were generated and compared using an advanced land surface hydrological scheme under development at Environment Canada. It was found that simple bias correction methods were capable of effectively downscaling SMOS observations to the a scale of 1 km without the loss of information from the satellite. A new bias correction method was also presented that was found to significantly outperform standard techniques.

The aim of this thesis is to characterize and discuss two kinds of influences on the outcome of a toxicological risk assessment. One kind of influence has to do with values and the role played by value-based judgment. Currently, many toxicological risk assessments are characterized by scientific uncertainties. When this is the case, risk assessors are to some extent dependent on assumptions and judgment, and this has consequences for the outcome of the assessment. Another other kind of influence comes from the quality and accuracy of the empirical studies that risk assessments are based on. If toxicological research and testing are affected by systematic errors (bias), this will influence the ensuing risk assessment. In order to improve toxicological risk assessments work must be done both on understanding and dealing with the impact of values and on getting better and more efficient methods for gathering facts. The two papers that make up this licentiate thesis may be seen as a contribution to each of these objectives. Article 1: Values in science and risk assessment It is a widely accepted claim that scientific practice contains valuejudgments, i.e. decisions made on the basis of values. This paper clarifies the concepts involved in this claim and explains its implications for risk assessment. It is explained why values are necessarily a part of science and of risk assessment. A certain type of values that contribute to the aim of science, so-called epistemic values, are identified as rationally justified as basis for judgment in science. It is argued that the aims of pure science and risk assessment differ in some aspects and that consequently pure science’s epistemic values are not sufficient for risk assessment. I suggest how the epistemic values may be supplemented in order to align better with the aim of risk assessment. Article 2: Bias in toxicology In this article, the potential for bias in toxicological research and in the performance of standardized toxicological testing in discussed. Due to the lack of empirical studies of bias in toxicology, very little is known aboutits prevalence and impact. Areas to consider for such studies are pointed out, and it is suggested that such investigations should be given priority. / QC 20101119

Explicit gender bias has been found using both experiments and field studies to favor men in hiring, promotion, and career opportunities (Eagly & Carli, 2007), but experimental studies have been criticized for over generalizing results obtained from a "stranger-to-stranger" paradigm (Copus, 2005; Landy, 2008). Landy (2008) argues that gender biases become negligible when raters are familiar with ratees. Additionally, Landy questioned the use of implicit measures to examine bias. Implicit or unconscious bias refers to a cognitive preference for one category over another, such as taking longer to associate female terms with managerial terms on a computerized task, and has also been shown to impact organizational decision making regarding women (Rudman & Kilianski, 2000). Implicit bias measures are often more predictive when bias may be socially undesirable. The goal of this research is to examine the effects of familiarity on automatic or unconscious gender bias. Study 1 examines associations between implicit and explicit measures of gender bias with evaluations of male and female job applicants who engage in agentic, negotiation behavior or not. It was expected that agentic (negotiating) female job applicants, compared to others, would suffer a backlash on ratings of communal traits and that this effect will be exacerbated by individual differences in implicit and explicit gender bias. An effect was found of negotiating being associated with higher agentic traits and lower overall ratings. Negotiating and gender did not interact, however the study did find women were rated as more communal than men. In Study 2 participants completed an Implicit Association Task (IAT) matching unfamiliar and familiar pictures of men and women with agentic and communal terms. It was expected that gender bias towards women would be stronger in the unfamiliar condition than in the familiar condition. Results indicated that there was a consistent bias against associating women with agentic terms and this effect was not influenced by familiarity. In Study 3, participants completed a gender-bias IAT and then read a scenario describing either a man or woman who is being evaluated for a promotion. They were asked to free recall positive and negative outcomes and attributes associated with the person in the scenario. It was expected that participants who have an implicit bias against women would remember negative events from the female scenario more easily than from the male scenario. There was a gender effect with participants remembering more negative events and less positive events when the employee was female compare to when the employee was male. Across all three studies differences were found between explicit and implicit measurements of gender bias. These three studies help us better understand relationships between implicit and explicit gender bias in the workplace. Additionally, Study 2 addressed criticism of gender bias findings ignoring familiarity.

Excerpt: The study by Terbeck et al. (2012) that was published in Psychopharmacology, Online First concluded that propranolol reduces implicit negative racial bias. However, this conclusion is not supported by the study because the implicit association test (IAT) (Greenwald et al. 2009) has not been sufficiently validated and because the claim for clinical treatment due to amygdala suppression is unsupported.

A defendant’s age can be an important determinant of judicial outcomes, but the perception of a defendant’s age can have implications for how these outcomes are determined. Research has suggested a connection between racial bias and age perception. This study sought to describe an age bias against African-Americans, and to connect this to jury sentencing outcomes. Undergraduate participants (N = 318) were recruited from university in the Appalachia region. First, participants estimated the ages of individuals in photographs. Analyses primarily focused on 18 and 19-year-old African-American and Caucasian males, but included a number of photographs from older males and females. Then, participants suggested a prison sentence in a mock jury sentencing task. African-Americans were estimated to be older than Caucasians by nearly four years (d = 1.75). This difference was present when controlling for exposure to African Americans, but with a negligible effect (d = 0.17). A modest increase (0.5 years, d = 0.32) was found in the sentence lengths assigned to African-American defendants. Discrepancies between age estimates and Page 112 2015 Appalachian Student Research Forum sentence lengths were not correlated. However logistic regression analyses found that age estimates of African-Americans were predictive of sentences exceeding state guidelines for this group, and the difference in age estimates between African-Americans and Caucasians was predictive of excessive sentences for both groups. While these regressions produced statistically significant (p < 0.05), the effect sizes of these regressions were negligible (d < 0.20). These findings suggest age bias is present and may have implications for juveniles and young adults in criminal proceedings.

Flickor har under lång tid varit marginaliserade inom forskningen kring den neuropsykiatriskafunktionsnedsättningen och tillika diagnosen ADHD vilket lett till att det vi idag vet om diagnosen oftaär könsspecifikt för pojkar. Då ADHD-symptomen hos flickor och pojkar ofta tar sig olika uttryck blirflickornas problematik svårare att identifiera. Konsekvenser av detta kan ses i att fler pojkar än flickorremitteras och utreds för ADHD och att många flickor som hade behövt stöd inte får det. Lärare står förmajoriteten av alla remitteringar till utredning av barn med förmodad ADHD och är ofta först ut attmisstänka en diagnos, varför det är viktigt att kunskapen om – och förståelsen för Flickor med ADHDväxer. Syftet med denna studie var att synliggöra flickor med ADHD genom att undersöka hur flickorssymptom på ADHD beskrivs inom forskningen, med vilka karakteristika diagnosen tar sig uttryck i enskolkontext samt vilken betydelse lärarens förståelse och förförståelse har för hur flickornauppmärksammas och bemöts. Genom en forskningsöversikt som integrerar befintlig forskning inomämnet söktes svaren på studiens två frågeställningar: Hur identifieras flickor med ADHD? samt Vilkaomgivande faktorer beskrivs som betydelsefulla för flickorna? Forskningen visade på en könsbias ilärares uppskattningar av elevers nedsättningar vilket resulterade i en remmiteringsbias. Forskningenvisade även på att flickors symptomyttringar var kontextuellt bundna och att flickorna utifrån desammanhang de vistas i därför kan uppfattas mer - eller mindre funktionsnedsatta, något som menaskunna bidra till underdiagnostiseringen av flickor med ADHD.

This dissertation investigates the question: are mission critical occupations more favored than other occupations in performance appraisals in pay pools? While many types of bias in performance appraisals occur, such as gender or race, occupational bias--favoring or showing preference for one occupation over another in performance appraisals and subsequent ratings-- has not been fully examined. There is a lack of empirical evidence that addresses occupational bias in performance appraisal and ratings in the Federal civil service sector, and more specifically the Department of Defense. The importance of occupational bias in performance appraisals is seen in the cost to organization and taxpayer, the degradation to fairness and trust in the workplace, and the erosion of organizational values. The methodology used to address this dissertation's hypothesis is a quantitative-qualitative inquiry that investigates performance ratings of the engineering occupational series within three Department of Defense (DOD) engineering agencies. The methodology is comprised of three parts: quantitative analysis of pay pool rating data and qualitative analysis of archived documents and expert interviews. Each part of the methodology is intended to be mutually supportive. The quantitative analysis yields a null finding of the hypothesis based on two findings. First, indicators of occupational bias were not found using differences of average occupational performance ratings between engineers and other occupations in three DOD engineering organizations. Second, Fiscal Year 2008 engineer occupational series performance ratings in three Department of Defense engineering agencies did not show statistically significant differences when compared to occupations such as personnel management specialists and accountants. This may be due to privacy act limitations in the data set used. Anecdotal evidence of preferences for mission critical occupations in performance appraisals and ratings was found to support the hypothesis. / Ph. D.

Automatic translation tools have facilitated navigating multilingual contexts, by providing accessible shortcuts for gathering, processing, and spreading information. As language technologies become more widely used and deployed on a large scale, however, their societal impact has sparked concern both within and outside the research community. This thesis adresses gender bias affecting Machine Translation (MT) and Speech Translation (ST) models. It contributes to this pressing area of research with an interdisciplinary perspective, to raise awareness of bias, improve the understanding of the phenomenon, and investigate best practices and methods to unveil and mitigate it in translation systems.