This thesis explores technical communication and seeks to establish that females outnumber males in the field while also holder more high-level positions. It further seeks to show why a field does not benefit from having one sex outnumber the other. The benefits of having an equal number of females and males contributing to the growth and expansion of the field are discussed. Finally, this thesis discusses potential pedagogical strategies which could be employed at the college level as a means of attracting more young men to the field and allowing for maximum growth of technical communication as a field of study and work. The thesis begins by exploring the history of technical communication as a means of understanding how it came to be a field where women outnumber men. It then briefly explores the differences between the learning styles of females and males as a means of demonstrating the importance of including both sexes equally. Lastly, using research from other, related fields pedagogical strategies are suggested for drawing more young males into the study and practice of technical communication. The conclusions drawn in this thesis are as follows: 1.) Women currently outnumber men in both the study and practice of technical communication. 2.) Research indicates that any field will benefit the most from including the skills and experiences of both sexes. 3.) Pedagogy may be effectively used as a means to help attract more young males into the field, thus increasing the growth and development of technical communication.

The purpose of my dissertation is to study an example of a depiction in local media of atroubled school. The dissertation examines the newspaper Sydsvenskan and its reports on thecase that developed from the events taking place around the Gustav Adolf’s school inLandskrona. The starting points for the media coverage began on the 18th of January 2007when the school was closed down. This paper follows Sydsvenskans reporting from that dayand the following fourteen days, until the 1st of February. The dissertation focuses onproblems such as bias and generalizations that arise in the media or more specifically inSydsvenskan during this event. The purpose of the dissertation is to examine how a singleturbulent event was portrayed in a large local newspaper and to see if the coverage wasbalanced. A variety of newspaper texts, ranging from articles, editorials and letters to theeditor are examined using critical discourse analysis, as developed by linguists NormanFairclough and Teun van Dijk. The method attempts to draw lines between the use oflanguage and the exercise of power. My results were divided in two sections, one on racismand one on political bias. Connecting the material to theories on hidden racism as describedby van Dijk and the Swedish sociologist Birgitta Löwander, I did not find the reports racist orstereotypical, in fact there are very few references to ethnic divisions in the material.However, there is a clear political bias regarding who is represented in the paper. Politiciansfrom Folkpartiet get more space in the reports than their political counterparts, They arefeatured in more than half of the articles. The political bias is not otherwise present in thecontent, and what is being said is more nuanced than who is actually saying it.

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Control and diagnosis of complex systems demand accurate knowledge of certain quantities to be able to control the system efficiently and also to detect small errors. Physical sensors are expensive and some quantities are hard or even impossible to measure with physical sensors. This has made model-based estimation an attractive alternative. Model-based estimators are sensitive to errors in the model and since the model complexity needs to be kept low, the accuracy of the models becomes limited. Further, modeling is hard and time consuming and it is desirable to design robust estimators based on existing models. An experimental investigation shows that the model deficiencies in engine applications often are stationary errors while the dynamics of the engine is well described by the model equations. This together with fairly frequent appearance of sensor offsets have led to a demand for systematic ways of handling stationary errors, also called bias, in both models and sensors. In the thesis systematic design methods for reducing bias in estimators are developed. The methods utilize a default model and measurement data. In the first method, a low order description of the model deficiencies is estimated from the default model and measurement data, resulting in an automatic model augmentation. The idea is then to use the augmented model for estimator design, yielding reduced stationary estimation errors compared to an estimator based on the default model. Three main results are: a characterization of possible model augmentations from observability perspectives, an analysis of what augmentations that are possible to estimate from measurement data, and a robustness analysis with respect to noise and model uncertainty. An important step is how the bias is modeled, and two ways of describing the bias are introduced. The first is a random walk and the second is a parameterization of the bias. The latter can be viewed as an extension of the first and utilizes a parameterized function that describes the bias as a function of the operating point of the system. The parameters, rather than the bias, are now modeled as random walks, which eliminates the trade-off between noise suppression in the parameter convergence and rapid change of the offset in transients. This is achieved by storing information about the bias in different operating points. A direct application for the parameterized bias is the adaptation algorithms that are commonly used in engine control systems. The methods are applied to measurement data from a heavy duty diesel engine. A first order model augmentation is found for a third order model and by modeling the bias as a random walk, an estimation error reduction of 50 % is achieved for a European transient cycle. By instead letting a parameterized function describe the bias, simulation results indicate similar, or better, improvements and increased robustness.

The purpose of this research was to investigate the relation between measurement bias at the item level (differential item functioning, dif) and predictive bias at the test score level. Dif was defined as a difference in the probability of getting a test item correct for examinees with the same ability but from different subgroups. Predictive bias was defined as a difference in subgroup regression intercepts and/or slopes in predicting a criterion. Data were simulated by computer. Two hypothetical subgroups (a reference group and a focal group) were used. The predictor was a composite score on a dimensionally complex test with 60 items. Sample size (35, 70, and 105 per group), validity coefficient (.3 or .5), and the mean difference on the predictor (0, .33, .66, and 1 standard deviation, sd) and the criterion (0 and .35 sd) were manipulated. The percentage of items showing dif (0%, 15%, and 30%) and the effect size of dif (small = .3, medium = .6, and large = .9) were also manipulated. Each of the 432 conditions in the 3 x 2 x 4 x 2 x 3 x 3 design was replicated 500 times. For each replication, a predictive bias analysis was conducted, and the detection of predictive bias against each subgroup was the dependent variable. The percentage of dif and the effect size of dif were hypothesized to influence the detection of predictive bias; hypotheses were also advanced about the influence of sample size and mean subgroup differences on the predictor and criterion. Results indicated that dif was not related to the probability of detecting predictive bias against any subgroup. Results were inconsistent with the notion that measurement bias and predictive bias are mutually supportive, i.e., the presence (or absence) of one type of bias is evidence in support of the presence (or absence) of the other type of bias. Sample size and mean differences on the predictor/criterion had direct and indirect effects on the probability of detecting predictive bias against both reference and focal groups. Implications for future research are discussed.

It has been shown that there exists a relationship between levels of metacognitive ability and estimation of personal ability for largely verbally-based tasks, where those with lessened facility for the task tend toward overestimation of their aptitude relative to their peers (Kruger and Dunning, 1999). This study examines this effect for a task of mechanical ability for volunteer participants (n = 69), where participants were given an abbreviated form of the Bennett Mechanical Comprehension Test (BMCT) to establish a level of competency. Following the administration of the BMCT, the participants were then asked to speculate on the hypothetical grade for their performance, as well as the relationship between their hypothetical grade, and the grades of others. Participants then "tutored" a hypothetical student on the solution to one of the problems found on the BMCT, and their explanations were coded for degree of bias towards confirmation versus disconfirmation that was utilized in the problem solving. It was found that females' basic ability had a greater range than males', and females on the high and low ends of competency made greater use of confirming strategies in their problem solving. This is indicative of the overall observed interaction effect between Gender, Perceived Relative Competence, and Actual Competence observed in this study.

The US Military requires specific fitness testing, known as the Physical Readiness Test (PRT), for its members to determine their overall fitness levels. The test currently being used has been shown to have bias towards heavier mass individuals of up to 20%. Prior research has been completed and several recommendations have been made to eliminate mass bias, but this has been conducted almost exclusively on males. There is very little data and research on military physical fitness testing for women besides combat specific evolution exercises. A possibility exists to eliminate the bias for females through implementing load carriage during PRT events. A specified load is to be placed on women while performing the PRT and compared to a non-loaded control test. The results should show if the load carriage devised has a beneficial effect on current testing methods through eliminating the mass bias for women.

This study investigates how women are affected by gender bias in the workplace. Despite the increasing numbers of women in the workforce, women are still under-represented and under-valued in workplaces, which, in part, is due to their gender stereotype. This study demonstrates how gender bias in the workplace has been proven to limit women in their careers and potential in their occupational roles. The media’s negative depiction of women in their gender stereotype reinforces and perpetuates this image as a cultural norm in society. Women both conform and are judged and evaluated according to their weak and submissive gender stereotype. Women face challenges and problems in the workplace when they are evaluated and appraised by their female gender stereotype. Women have been prevented from acquiring jobs and positions, have been denied promotions and advancements, failed to be perceived as desiring of and capable of leadership or management positions, as well as typically receive lower paid than their male counterparts. Furthermore, women’s unique, indirect, and congenial conversational methods are perceived as unconfident, incompetent, and thus, incapable in the masculine organizational culture of most workplaces. Through the investigation of gender bias in the workplace, professionals and employers will gain an awareness of how gender bias and socially-prescribed gender roles can affect the workplace and interfere with women’s success in their career. Technical communicators and other educators will have a better understanding of how to overcome gender stereotyping and be encouraged to teach students on how to be gender-neutral in their communications in the workplace, perhaps striving for a more egalitarian society.

Over the past few decades, there has been an exponential increase of females holding professional positions traditionally assigned to males. While female professors of music have become more commonplace over the past few decades, there continues to be a recognizable absence of women in the field of music composition. Additionally, publication and performance of music composed by women is minimal in comparison to their male counterparts. The purpose of this study was to examine the current employment practices of U.S. universities with leading music programs to ascertain if gender inequity was evident. Further, I sought to determine what social barriers cisgender female professors faced when pursuing a degree in composition and what restrictions they have faced as professional composers. Finally, I ascertained what initiatives are in place to encourage women to pursue careers in music composition. Cisgender music composition professors at leading music programs in the U.S. (N=14) were interviewed, and the conversations were recorded, transcribed, and coded to expose common themes. Although participants indicated the road to professorship was not significantly affected by gender, they reported encountering pro-male prejudice when seeking to publish, produce, program, and distribute their musical works. The interviews also revealed that issues surrounding motherhood and ageism led to restrictions in their advancement in academia. Further research focusing on causes of continued marginalization of musical works by females and university employment practices surrounding the hiring of female composition professors could provide a broader view of the political and social issues that affect women composers’ careers today.

Understanding police use of lethal force requires the collection of reliable data. Due to bias present in police-use-of-lethal-force databases, researchers typically triangulate using multiple data sources to compensate for this bias; however, triangulation is restricted when the bias present in each database is unknown. This study investigates three government-funded and three independent police-use-of-lethal-force databases to identify methodological sources of bias present in the major U.S. data-collection systems. Bias was coded based on nine categories, including misclassification bias, broad conceptualization, narrow conceptualization, overlap bias, coverage bias, voluntary response bias, observer bias, gatekeeping bias, and self-report response bias. Findings suggest that all six databases had at least three different types of methodological bias present. Generally, public, government-sponsored databases exhibit bias through data self-reporting by law enforcement and varying victim race determination methods. Private databases reveal bias through media-based reporting and the triangulation of data from multiple sources, which is further complicated by lack of transparency in the databases' design and administrative procedures. All six databases have a unique position to the State, which should also inform researcher data selection. I argue that selecting data sources that complement each other based on these identified biases will produce a more complete image of police-use-of-lethal-force and enhance finding accuracy in future research. / Master of Science / Understanding incidents where a civilian dies due to the actions of police officers requires the collection of reliable data. Due to bias—flaws in the data collection methods or data presentation—which lead to varying results when using different databases, researchers typically use multiple data sources to make up for these flaws; however, this method is restricted when the bias present in each database is unknown. This study investigates three government-funded and three independent police-use-of-lethal-force databases to identify sources of bias present in the major U.S. data-collection systems. Findings suggest that all six databases had at least three different types of flaws present. Generally, public, government-sponsored databases exhibit bias through police self-reporting lethal force, where an officer's department reports the officer's actions and there is no individual or group outside of the police reporting these incidents. Additionally, there is a flaw in how police record the race of a victim, who dies through police use of lethal force; Varying procedures in how race is recorded, whether recorded based on the officer's opinion or where a victim self-reports their own race prior to death on a government data system such as the Department of Motor Vehicles, also impacts the race data included in public databases. Private databases reveal bias through collecting incident data from news reports and using data from multiple sources such as law enforcement reports, medical examiner reports, and media reports simultaneously; this is further complicated by lack of transparency in the databases' design and administrative procedures, where there are no documents detailing the steps databases take in collecting and presenting data. All six databases have a unique position to the U.S. Government, where some are funded by the Government and where some are motivated by recent high profile police killings, which should impact researcher data selection. Ideally, the databases used should hold multiple perspectives or positions to the Government to provide an more complete image of lethal force. I argue that selecting data sources that complement each other based on these identified biases will produce a more complete image of police-use-of-lethal-force and enhance finding accuracy in future research.