Search results for: social bias

Authors: Kellina Craig-Henderson

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Today, there is increased attention to the role of social perceptions in the selection, hiring, and management of employees and the evaluation and promotion of students. In some contexts, where women or members of certain social groups have been historically underrepresented there is evidence that these perceptions reflect the implicit biases people harbor. Research in the social and psychological sciences reveals that implicit biases against women unfairly disadvantage them in academic and work settings. This presentation will provide an overview of the current state of knowledge on an implicit bias as well as the problems associated with it. How employers, educators and other evaluators can inoculate themselves from the pernicious effects of these biases will be considered.

Keywords: gender equity, implicit bias, social psychology, unconscious bias

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Authors: Susanna Menis

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‘Unconscious’ bias is widespread, affecting society on all levels of decision-making and beyond. Placed in the law context, this study will explore the direct effect of the psycho-social and cultural evolution of unconscious bias on how a judicial decision was made. The aim of this study is to contribute to socio-legal scholarship by examining the formation of unconscious bias and its influence on the creation of legal rules that judges believe reflect social solidarity and protect against violence. The study seeks to understand how concepts like criminalization and unlawfulness are constructed by the common law. The study methodology follows two theoretical approaches: historical genealogy and emotions as sociocultural phenomena. Both methods have the ‘tracing back’ of the original formation of a social way of seeing and doing things in common. The significance of this study lies in the importance of reflecting on the ways unconscious bias may be formed; placing judges’ decisions under this spotlight forces us to challenge the status quo, interrogate justice, and seek refinement of the law.

Keywords: legal geneology, emotions, disgust, criminal law

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Authors: Ahmad Al-Omari, Osama Khreis, Ahmad M. K. Dagamseh, Abdullah Ababneh, Kevin Lear

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High-speed infrared vertical-cavity surface-emitting laser diodes (VCSELs) with Cu-plated heat sinks were fabricated and tested. VCSELs with 10 mm aperture diameter and 4 mm of electroplated copper demonstrated a -3dB modulation bandwidth (f_-3dB) of 14 GHz and a resonance frequency (f_R) of 9.5 GHz at a bias current density (J_bias) of only 4.3 kA/cm², which corresponds to an improved f_-3dB²/J_bias ratio of 44 GHz²/kA/cm². At higher and lower bias current densities, the f_-3dB²/ J_bias ratio decreased to about 30 GHz²/kA/cm² and 18 GHz²/kA/cm², respectively. Examination of the analogue modulation response demonstrated that the presented VCSELs displayed a steady f_-3dB/ f_R ratio of 1.41±10% over the whole range of the bias current (1.3I_th to 6.2I_th). The devices also demonstrated a maximum modulation bandwidth (f_{-3dB max}) of more than 16 GHz at a bias current less than the industrial bias current standard for reliability by 25%.

Keywords: current density, high-speed VCSELs, modulation bandwidth, small-signal characteristics, thermal impedance, vertical-cavity surface-emitting lasers

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Authors: Rui G. Serôdio, Carina Martins, Alexandra Serra, José A. Lima, Luísa Catita, Paula Lopes

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Building on social identity approach, we tested the impact of social categorization and comparison in the psychosocial process by which social entrepreneurs define their group identity. Specifically, we address how both differentiation and assimilation processes are set of in the context of constructing a novel, distinctive and socially salient – social entrepreneurs. As part of a larger research line, a quasi-experimental study with Social and Business Entrepreneurs, as well as “Lay People” provided evidence consistent with our predictions: (1) Social Entrepreneurs, in contrast with Lay People and Business Entrepreneurs, value more strongly social identity than personal identity, and the later is the only group that values Personal Differentiation; (2) unlike Entrepreneurs, Social Entrepreneurs display an ingroup bias across group evaluations; (3) Lay People, display a self-serving bias, although, overall, they allocate a more positive image to the target groups; (4) combining own vs. others evaluations across all groups, Social Entrepreneurs receive the more positive value. From the standpoint of social identity and self-categorization theories and their approach to group process, we discuss the processes of intergroup comparison and differentiation as core processes in the construction of a positive social identity. We illustrate it within the context of social entrepreneurship, a political and social “wave” that flows across Europe at this time.

Keywords: group processes, social entrepreneurship, social identity, business entrepreneurs

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Authors: Jou-An Chung

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The purpose of this study is to investigate the verb bias of the Mandarin verbs in children’s reading materials and provide the criteria for categorization. Verb bias varies cross-linguistically. As Mandarin and English are typological different, this study hopes to shed light on Mandarin verb bias with the use of corpus and provide thorough and detailed criteria for analysis. Moreover, this study focuses on children’s reading materials since it is a significant issue in understanding children’s sentence processing. Therefore, investigating verb bias of Mandarin verbs in children’s reading materials is also an important issue and can provide further insights into children’s sentence processing. The small corpus is built up for this study. The corpus consists of the collection of school textbooks and Mandarin Daily News for children. The files are then segmented and POS tagged by JiebaR (Chinese segmentation with R). For the ease of analysis, the one-word character verbs and intransitive verbs are excluded beforehand. The total of 20 high frequency verbs are hand-coded and are further categorized into one of the three types, namely DO type, SC type and other category. If the frequency of taking Other Type exceeds the threshold of 25%, the verb is excluded from the study. The results show that 10 verbs are direct object bias verbs, and six verbs are sentential complement bias verbs. The paired T-test was done to assure the statistical significance (p = 0.0001062 for DO bias verb, p=0.001149 for SC bias verb). The result has shown that in children’s reading materials, the DO biased verbs are used more than the SC bias verbs since the simplest structure of sentences is easier for children’s sentence comprehension or processing. In sum, this study not only discussed verb bias in child's reading materials but also provided basic coding criteria for verb bias analysis in Mandarin and underscored the role of context. Sentences are easier for children’s sentence comprehension or processing. In sum, this study not only discussed verb bias in child corpus, but also provided basic coding criteria for verb bias analysis in Mandarin and underscored the role of context.

Keywords: corpus linguistics, verb bias, child language, psycholinguistics

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Authors: Sumachaya Harnsukworapanich, Tetsuo Ichimori

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The apportionment method is used by many countries, to calculate the distribution of seats in political bodies. For example, this method is used in the United States (U.S.) to distribute house seats proportionally based on the population of the electoral district. Famous apportionment methods include the divisor methods called the Adams Method, Dean Method, Hill Method, Jefferson Method and Webster Method. Sometimes the results from the implementation of these divisor methods are unfair and include errors. Therefore, it is important to examine the optimization of this method by using a bias measurement to figure out precise and fair results. In this research we investigate the bias of divisor methods in the U.S. Houses of Representatives toward large and small states by applying the Stolarsky Mean Method. We compare the bias of the apportionment method by using two famous bias measurements: The Balinski and Young measurement and the Ernst measurement. Both measurements have a formula for large and small states. The Third measurement however, which was created by the researchers, did not factor in the element of large and small states into the formula. All three measurements are compared and the results show that our measurement produces similar results to the other two famous measurements.

Keywords: apportionment, bias, divisor, fair, measurement

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Authors: Katie Strong, Brian P. O'Connor, Jacqueline M. Kanippayoor

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To date, self-report measures of psychopathy have largely been conceptualized with a male-focused understanding of the disorder, with the presumption that psychopathy expression is uniform across genders. However, generalizing this understanding to the female population may be misleading. The objective of this research was to explore gender differences in the expression of psychopathy and to assess current self-report psychopathy measures for gender bias. It was hypothesized that some items in commonly used measures of psychopathy may show gender bias and that existing measures may not contain enough items that are relevant to the manifestation of psychopathy in women. An exploratory investigation was conducted on statistical bias in common measures of psychopathy, and novel, relevant, but previously neglected items and measures were included in a new data collection. The participant pool included a sample of 403 university students and 354 participants recruited using Amazon Mechanical Turk. Item Response Theory methods - including Differential Item Functioning - were used to assess for the item- and test- level bias across several common self-report measures of psychopathy. Analyses indicated occasional and modest levels of item-level bias, and that some additional female-relevant items merit consideration for inclusion in measures of psychopathy. These findings suggest that current self-report measures of psychopathy may be demonstrating gender-bias and warrant further examination.

Keywords: gender, measurement bias, personality, psychopathy

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: Amber Lim, Ted Ruffman

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A vast amount of research evidence indicates that children develop social attitudes that are similar to those of their parents. When using general measures of social attitudes, such as social dominance orientation (SDO), right-wing authoritarianism (RWA), and prejudice, studies show that parents' and children’s attitudes were correlated. However, the mechanisms behind the intergenerational transmission of attitudes remain largely unexplained. Since it was speculated that the origins of RWA could be traced back to one’s relationship with their parents, the aim of this study was to assess how parents’ social attitudes and parenting behavior are related to children’s social development. One line of research suggests that the different ways in which authoritarian and authoritative parents reason with their children may impact Theory of Mind (ToM) development. That is, inductive discipline (e.g., emphasising how the child’s actions affect others) facilitates empathy and ToM development. Conversely, past evidence shows that children have poorer ToM development when parents enforce rules without explanation. Thus, this study addresses the question of how parent behavior plays a role in the gradual acquisition of a ToM and social attitudes. Seventy parents reported their social attitudes, parenting behavior, and their child’s mental state and non-mental state vocabulary. Their children were given ToM and perspective-taking tasks, along with a friend choice task to measure racial bias and anti-fat bias. As hypothesised, parents’ use of inductive reasoning correlated with children’s performance on Theory of Mind tasks. Mothers’ inductive reasoning facilitated children’s acquisition of mental state vocabulary. Parents’ autonomy granting was associated with improved mental state vocabulary. Authoritarian parenting traits such as verbal hostility were linked to children’s racial bias. These findings highlight the importance of parent-child discussion in shaping children’s social understanding.

Keywords: parenting style, prejudice, social attitudes, social understanding, theory of mind

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Authors: Adriana Avila Zuniga Nordfjeld

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This paper provides a literature review to document the state of the art with respect to handling 'human bias' in decision making within the established quality management systems (QMS) and LEAN theory, in the context of shipbuilding. Previous research shows that in shipbuilding there is a huge deviation from the planned man-hours under the project management to the actual man-hours used because of errors in planning and reworks caused by human bias in the information flows among others. This reduces the efficiency and increases operational costs. Thus, the research question is how QMS and LEAN handle biases. The findings show the gap in studying the integration of methods to handle human bias in decision making into QMS and lean, not only within shipbuilding but also in general. Theoretical and practical implications are discussed for researchers and practitioners in the areas of decision making QMS, LEAN, and future research is suggested.

Keywords: human bias, decision making, LEAN shipbuilding, quality management systems

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Authors: Reza Aghayan

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This paper illustrates that numerically invariant joint signatures suffer biases in the resulting signatures. Next, we classify the arising biases as Bias Type 1 and Bias Type 2 and show how they can be removed.

Keywords: Euclidean and affine geometries, differential invariant signature curves, numerically invariant joint signatures, numerical analysis, numerical bias, curve analysis

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Authors: Yeşim Özer Özkan, Fatma Büşra Fincan

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Biased sample is a regression of an observation, design process and all of the specifications lead to tendency of a side or the situation of leaving from the objectivity. It is expected that, test items are answered by the students who come from different social groups and the same ability not to be different from each other. The importance of the expectation increases especially during student selection and placement examinations. For example, all of the test items should not be beneficial for just a male or female group. The aim of the research is an investigation of item bias whether or not the exam included in 2014 free boarding and scholarship examination in terms of gender variable. Data which belong to 5th, 6th, and 7th grade the secondary education students were obtained by the General Directorate of Measurement, Evaluation and Examination Services in Turkey. 20% students were selected randomly within 192090 students. Based on 38418 students’ exam paper were examined for determination item bias. Winsteps 3.8.1 package program was used to determine bias in analysis of data, according to Rasch Model in respect to gender variable. Mathematics items tests were examined in terms of gender bias. Firstly, confirmatory factor analysis was applied twenty-five math questions. After that, NFI, TLI, CFI, IFI, RFI, GFI, RMSEA, and SRMR were examined in order to be validity and values of goodness of fit. Modification index values of confirmatory factor analysis were examined and then some of the items were omitted because these items gave an error in terms of model conformity and conceptual. The analysis shows that in 2014 free boarding and scholarship examination exam does not include bias. This is an indication of the gender of the examination to be made in favor of or against different groups of students.

Keywords: gender, item bias, placement test, Rasch model

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Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

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The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

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Authors: Helen J. Spray, Karina J. Linnell

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Local-global bias in adulthood is strongly dependent on environmental factors and a global bias is not the universal characteristic of adult perception it was once thought to be: whilst Western adults typically demonstrate a global bias, Namibian adults living in traditional villages possess a strong local bias. Furthermore, environmental effects on local-global bias have been shown to be highly gender-specific; whereas urbanisation promoted a global bias in urbanised Namibian women but not men, education promoted a global bias in urbanised Namibian men but not women. Adult populations, however, provide only a snapshot of the gene-environment interactions which shape perceptual bias. Yet, to date, there has been little work on the development of local-global bias across environmental settings. In the current study, local-global bias was assessed using a similarity-matching task with Navon figures in children aged between 4 and 15 years from across three populations: traditional Namibians, urban Namibians, and urban British. For the two Namibian groups, measures of urbanisation and education were obtained. Data were subjected to both between-group and within-group analyses. Between-group analyses compared developmental trajectories across population and gender. These analyses revealed a global bias from even as early as 4 in the British sample, and showed that the developmental onset of a global bias is not fixed. Urbanised Namibian children ultimately developed a global bias that was indistinguishable from British children; however, a global bias did not emerge until much later in development. For all populations, the greatest developmental effects were observed directly following the onset of formal education. No overall gender effects were observed; however, there was a significant gender by age interaction which was difficult to reconcile with existing biological-level accounts of gender differences in the development of local-global bias. Within-group analyses compared the effects of urbanisation and education on local-global bias for traditional and urban Namibian boys and girls separately. For both traditional and urban boys, education mediated all effects of age and urbanisation; however, this was not the case for girls. Traditional Namibian girls retained a local bias regardless of age, education, or urbanisation, and in urbanised girls, the development of a global bias was not attributable to any one factor specifically. These results are broadly consistent with aforementioned findings that education promoted a global bias in urbanised Namibian men but not women. The development of local-global bias does not follow a fixed trajectory but is subject to environmental control. Understanding how variability in the development of local-global bias might arise, particularly in the context of gender, may have far-reaching implications. For example, a number of educationally important cognitive functions (e.g., spatial ability) are known to show consistent gender differences in childhood and local-global bias may mediate some of these effects. With education becoming an increasingly prevalent force across much of the developing world it will be important to understand the processes that underpin its effects and their implications.

Keywords: cross-cultural, development, education, gender, local-global bias, perception, urbanisation, urbanization

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Authors: Cory A. Logston

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It is imperative researchers continue to explore every transformative strategy to increase empathy and awareness of racial bias. Racism is a social and political concept that uses stereotypical ideology to highlight racial inequities. Everyone has biases they may not be aware of toward disparate out-groups. There is some form of racism in every profession; doctors, lawyers, and teachers are not immune. There have been numerous successful and unsuccessful strategies to motivate and transform an individual’s unconscious biased attitudes. One method designed to induce a transformative experience and identify implicit bias is virtual reality (VR). VR is a technology designed to transport the user to a three-dimensional environment. In a virtual reality simulation, the viewer is immersed in a realistic interactive video taking on the perspective of a Black man. The viewer as the character experiences discrimination in various life circumstances growing up as a child into adulthood. For instance, the prejudice felt in school, as an adolescent encountering the police and false accusations in the workplace. Current research suggests that an immersive VR simulation can enhance self-awareness and become a transformative learning experience. This study uses virtual reality immersion and transformative learning theory to create empathy and identify any unintentional racial bias. Participants, White teachers, will experience a VR immersion to create awareness and identify implicit biases regarding Black students. The desired outcome provides a springboard to reconceptualize their own implicit bias. Virtual reality is gaining traction in the research world and promises to be an effective tool in the transformative learning process.

Keywords: empathy, implicit bias, transformative learning, virtual reality

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Authors: X. L. Zhou, S. Tunmee, I. Toda, K. Komatsu, S. Ohshio, H. Saitoh

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Hydrogenated amorphous carbon (a-C:H) films have been synthesized by a radio frequency plasma enhanced chemical vapor deposition (rf-PECVD) technique with different bias voltage from 0.0 to -0.5 kV. The Raman spectra displayed the polymer-like hydrogenated amorphous carbon (PLCH) film with 0.0 to -0.1 and a-C:H films with -0.2 to -0.5 kV of bias voltages. The surface chemical information of all films were studied by X-ray photo electron spectroscopy (XPS) technique, presented to C-C (sp2 and sp3) and C-O bonds, and relative carbon (C) and oxygen (O) atomics contents. The O contamination had affected on structure and optical properties. The true density of PLCH and a-C:H films were characterized by X-ray refractivity (XRR) method, showed the result as in the range of 1.16-1.73 g/cm3 that depending on an increasing of bias voltage. The hardness was proportional to the true density of films. In addition, the optical properties i.e. refractive index (n) and extinction coefficient (k) of these films were determined by a spectroscopic ellipsometry (SE) method that give formation to in 1.62-2.10 (n) and 0.04-0.15 (k) respectively. These results indicated that the optical properties confirmed the Raman results as presenting the structure changed with applied bias voltage increased.

Keywords: negative bias voltage, a-C:H film, oxygen contamination, optical properties

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Authors: Koustav Pal, Indranil Das

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In recent times, perovskite and double perovskite (DP) systems attracts lot of interest as they provide a rich material platform for studying emergent functionalities like near-room-temperature ferromagnetic (FM) insulators, exchange bias (EB), magnetocaloric effects, colossal magnetoresistance, anisotropy, etc. These interesting phenomena emerge because of complex couplings between spin, charge, orbital, and lattice degrees of freedom in these systems. Various magnetic phenomena such as exchange bias, spin glass, memory effect, colossal magneto-resistance, etc. can be modified and controlled through antisite (B-site) disorder or controlling oxygen concentration of the material. By controlling oxygen concentration in SrFe0.5Co0.5O3 – δ (SFCO) (δ ∼ 0.3), we achieve intrinsic exchange bias effect with a large exchange bias field (∼1.482 Tesla) and giant coercive field (∼1.454 Tesla). Now we modified the B-site by introducing 10% iridium in the system. This modification give rise to the exchange bias field as high as 1.865 tesla and coercive field 1.863 tesla. Our work aims to investigate the effect of oxygen deficiency and B-site effect on exchange bias in oxide materials for potential technological applications. Structural characterization techniques including X-ray diffraction, scanning tunneling microscopy, and transmission electron microscopy were utilized to determine crystal structure and particle size. X-ray photoelectron spectroscopy was used to identify valence states of the ions. Magnetic analysis revealed that oxygen deficiency resulted in a large exchange bias due to a significant number of ionic mixtures. Iridium doping was found to break interaction paths, resulting in various antiferromagnetic and ferromagnetic surfaces that enhance exchange bias.

Keywords: coercive field, disorder, exchange bias, spin glass

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Authors: Arnab Majumdar, Srimani Sen

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In this paper, a vivid simulated study has been made on 35 GHz Ka-band window frequency in order to judge and compare the DC and high frequency properties of cubic ZnB-GaN with the existing hexagonal 4H-SiC. A flat profile p⁺pnn⁺ DDR structure of impatt is chosen and is optimized at a particular bias current density with respect to efficiency and output power taking into consideration the effect of mobile space charge also. The simulated results obtained reveals the strong potentiality of impatts based on both cubic ZnB-GaN and hexagonal 4H-SiC. The DC-to-millimeter wave conversion efficiency for cubic ZnB-GaN impatt obtained is 50% with an estimated output power of 2.83 W at an optimized bias current density of 2.5×10⁸ A/m². The conversion efficiency and estimated output power in case of hexagonal 4H-SiC impatt obtained is 22.34% and 40 W respectively at an optimum bias current density of 0.06×10⁸ A/m².

Keywords: cubic ZnB-GaN, hexagonal 4H-SiC, double drift impatt diode, millimetre wave, optimised bias current density, wide band gap semiconductor

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Authors: Isaac Mugume

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Since the beginning of the 21st century, climate change has been an issue due to the reported rise in global temperature and changes in the frequency as well as severity of extreme weather and climatic events. The changing climate has been attributed to rising concentrations of greenhouse gases, including environmental changes such as ecosystems and land-uses. Climatic projections have been carried out under the auspices of the intergovernmental panel on climate change where a couple of models have been run to inform us about the likelihood of future climates. Since one of the major forcings informing the changing climate is emission of greenhouse gases, different scenarios have been proposed and future climates for different periods presented. The global climate models project different areas to experience different impacts. While regional modeling is being carried out for high impact studies, bias correction is less documented. Yet, the regional climate models suffer bias which introduces uncertainty. This is addressed in this study by bias correcting the regional models. This study uses the Weather Research and Forecasting model under different representative concentration pathways and correcting the products of these models using observed climatic data. This study notes that bias correction (e.g., the running-mean bias correction; the best easy systematic estimator method; the simple linear regression method, nearest neighborhood, weighted mean) improves the climatic projection skill and therefore reduce the uncertainty inherent in the climatic projections.

Keywords: bias correction, climatic projections, numerical models, representative concentration pathways

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Justine McKay

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Implicit Bias and its impact on the schooling experience of racial minorities with ADHD is significant. ADHD has become a globally diagnosed disorder. The lack of an objective diagnostic tool for ADHD has created controversy over the disease and its validity. ADHD is referred to as a social construct or a suburban problem related to active white boys who disrupt classrooms. The subjectivity of an ADHD diagnosis and the diagnostic process is based on norm-referenced checklists of behaviours completed by the student, caregiver, teachers, clinicians, and other community members. Teachers' perceptions of classroom behaviours are influenced by implicit bias related to race and socioeconomic status. The same behaviours displayed by white and marginalized or low-income students are perceived differently. The white student is perceived to be struggling academically and needing support, while the marginalized or lower-income student's behaviour is seen as disruptive or criminal. The presence of teacher implicit bias results in the inequity of diagnosis, and academic support, which has long-term implications for these students. The subjectivity of the diagnostic process socially reproduces the systemic injustice of opportunity for marginalized youth within the education system.

Keywords: ADHD, education, equity, implicit bias, subjectivity

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Authors: Juliana Guimarães Faria

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The article focus on social networks and deaf people. It aims to analyze the studies done about this topic published in journals, as well as the ones done through dissertations and theses. It also aims to identify the thematic focus of the studies produced and to identify how the deaf relates to social networks, more specifically, trying to identify, starting with those productions, what are the benefits, or not, of social networks for the deaf and if there is some reflection about the way the deaf community has been organizing politically in search of bilingual education and inclusion, making use of the softwares of social networks. After reading, description and analysis of the eleven works identified about social networks and the deaf, we detected three thematic groups: four studies presented discussions about social networks and the socialization of the deaf; four works presented discussions about the contribution of social networks to the linguistic and cognitive development of the deaf; and three works presented discussions about the political bias of the use of social networks in favor of the deaf. We also identified that the works presented an optimistic view of social networks.

Keywords: social networks, deaf, internet, Brazil

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Authors: Amrin Moger, Sagar Bhalerao, Martin Mathew

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Advertisements play a vital role in dissemination of information regarding products and services. Advertisements as Mass Media tool is not only a source of entertainment, but also a source of information, education and entertainment. It provides information about the outside world and exposes us to other ways of life and culture. Public service advertisements (PSA) are generally aimed at public well-being. Aim of PSA is not to make profit, but rather to change public opinion and raise awareness in the Society about a social issue.’ Start with the boys’ is one such PSA aims to create awareness about issue of ‘gender bias’ that is taught prevalent in the society. Persons with disabilities (PWDs) are also consumers of PSA in the society. The population of persons with disability in the society also faces gender bias and discrimination. It is a double discrimination. The advertisement selected for the study gives out a strong message on gender bias and therefore must be accessible to everyone including PWDs in the society. Accessibility of PSA in the digital format can be done with the help of Universal Design (UD) in digital media application. Features of UD inclusive in nature, and it focus on eliminating established barriers through initial designs. It considers the needs of diverse people, whether they are persons with or without disability. In this research two aspects of UD in digital media: captioning and Indian sign language (ISL) is used. Hence a short survey study was under taken to know the effects of a multimedia on gender bias, in accessible format on persons with and without disability. The result demonstrated a significant difference in the opinion, on the usage accessible and non-accessible format for persons with and without disability and their understanding of message in the PSA selected for the study.

Keywords: public service advertisements, gender, disability, accessibility

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Authors: Keyao Li, Sai On Cheung

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Incorporation of alternative dispute resolution (ADR) mechanism has been the main feature of current trend of construction project dispute resolution (CPDR). ADR approaches have been identified as efficient mechanisms and are suitable alternatives to litigation and arbitration. Moreover, the use of ADR in this multi-tiered dispute resolution process often leads to repeated evaluations of a same dispute. Multi-tiered CPDR may become a breeding ground for cognitive biases. When completed knowledge is not available at the early tier of construction dispute resolution, disputing parties may form preconception of the dispute matter or the counterpart. This preconception would influence their information processing in the subsequent tier. Disputing parties tend to search and interpret further information in a self-defensive way to confirm their early positions. Their imbalanced information collection would boost their confidence in the held assessments. Their attitudes would be hardened and difficult to compromise. The occurrence of cognitive bias, therefore, impedes efficient dispute settlement. This study aims to explore ways to minimize bias in CPDR. Based on a comprehensive literature review, three types of bias minimizing approaches were collected: strategy-based, attitude-based and process-based. These approaches were further operationalized into bias minimizing measures. To verify the usefulness and practicability of these bias minimizing measures, semi-structured interviews were conducted with ten CPDR third party neutral professionals. All of the interviewees have at least twenty years of experience in facilitating settlement of construction dispute. The usefulness, as well as the implications of the bias minimizing measures, were validated and suggested by these experts. There are few studies on cognitive bias in construction management in general and in CPDR in particular. This study would be the first of its type to enhance the efficiency of construction dispute resolution by highlighting strategies to minimize the biases therein.

Keywords: bias, construction project dispute resolution, minimization, multi-tiered, semi-structured interview

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Authors: Guiheng Zhang, Wei Zhang, Jun Fu, Yudong Wang

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A 900 MHz three-stage SiGe power amplifier (PA) with high power gain is presented in this paper. Volterra Series is applied to analyze nonlinearity sources of SiGe HBT device model clearly. Meanwhile, the influence of operating current to IMD3 is discussed. Then a β-helper current mirror bias circuit is applied to improve linearity, since the β-helper current mirror bias circuit can offer stable base biasing voltage. Meanwhile, it can also work as predistortion circuit when biasing voltages of three bias circuits are fine-tuned, by this way, the power gain and operating current of PA are optimized for best linearity. The three power stages which fabricated by 0.18 μm SiGe technology are bonded to the printed circuit board (PCB) to obtain impedances by Load-Pull system, then matching networks are done for best linearity with discrete passive components on PCB. The final measured three-stage PA exhibits 21.1 dBm of output power at 1 dB compression point (OP1dB) with power added efficiency (PAE) of 20.6% and 33 dB power gain under 3.3 V power supply voltage.

Keywords: high gain power amplifier, linearization bias circuit, SiGe HBT model, Volterra series

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Authors: Chih-Hsiang Chang, Pei-Shan Kao

Abstract:

This paper discusses the reaction of investors in the Taiwan stock market to the most probable unknown earnings-related information and the most probable known earnings-related information. As compared with the previous literature regarding the effect of an official announcement of earnings forecast revision, this paper further analyzes investors’ cognitive bias toward the unknown and known earnings-related information, and the role of media during the investors' reactions to the foresaid information shocks. The empirical results show that both the unknown and known earnings-related information provides useful information content for a stock market. In addition, cognitive bias and disposition effect are the behavioral pitfalls that commonly occur in the process of the investors' reactions to the earnings-related information. Finally, media coverage has a remarkable influence upon the investors' trading decisions.

Keywords: cognitive bias, role of media, disposition effect, earnings-related information, behavioral pitfall

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Authors: Belkacem Laimouche

Abstract:

With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

Abstract:

Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder bias voltage, switching voltage, radio-over-fiber, RF gain

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Authors: Hyungil Chae

Abstract:

This work presents a method to reduce spinning current of a Hall-effect sensor for low-power magnetic sensor applications. Spinning current of a Hall-effect sensor changes the direction of bias current periodically and can separate signals from DC-offset. The bias current is proportional to the sensor sensitivity but also increases the power consumption. To achieve both high sensitivity and low power consumption, the bias current can be pulse-width modulated. When the bias current duration Tb is reduced by a factor of N compared to the spinning current period of Tₛ/2, the total power consumption can be saved by N times. N can be large as long as the Hall-effect sensor settles down within Tb. The proposed scheme is implemented and simulated in a 0.18um CMOS process, and the power saving factor is 9.6 when N is 10. Acknowledgements: This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (20160001360022003, Development of Hall Semi-conductor for Smart Car and Device).

Keywords: chopper stabilization, Hall-effect sensor, pulse width modulation, spinning current

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Authors: Bronwen Wade

Abstract:

Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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