A Model for Prejudiced Learning in Noisy Environments

Based on the heuristics that maintaining presumptions can be beneficial in uncertain environments, we propose a set of basic axioms for learning systems to incorporate the concept of prejudice. The simplest, memoryless model of a deterministic learning rule obeying the axioms is constructed, and shown to be equivalent to the logistic map. The system's performance is analysed in an environment in which it is subject to external randomness, weighing learning defectiveness against stability gained. The corresponding random dynamical system with inhomogeneous, additive noise is studied, and shown to exhibit the phenomena of noise induced stability and stochastic bifurcations. The overall results allow for the interpretation that prejudice in uncertain environments entails a considerable portion of stubbornness as a secondary phenomenon.Comment: 21 pages, 11 figures; reduced graphics to slash size, full version on Author's homepage. Minor revisions in text and references, identical to version to be published in Applied Mathematics and Computatio

Competition and Gender Prejudice: Are Discriminatory Employers Doomed to Fail?

According to Becker's (1957) famous theory on discrimination, entrepreneurs with a strong prejudice against female workers forgo profits by submitting to their tastes. In a competitive market their firms lack efficiency and are therefore forced to leave. We present new empirical evidence for this prediction by studying the survival of startup firms in a large longitudinal matched employer-employee data set from Austria. Our results show that firms with strong preferences for discrimination, i.e. a low share of female employees relatively to the industry average, have significantly shorter survival rates. This is especially relevant for firms starting out with female shares in the lower tail of the distribution. They exit about 18 months earlier than firms with a median share of females. We see no differences in survival between firms at the top of the female share distribution and at the median, though. We further document that highly discriminatory firms that manage to survive submit to market powers and increase their female workforce over time.Firm survival, profitability, female employment, discrimination, market test, matched employer-employee data

The Law and Economics of Antidiscrimination Law

This essay provides an overview of the central theoretical law and economics insights concerning antidiscrimination law across a variety of contexts including discrimination in labor markets, housing markets, consumer purchases, and policing. The different models of discrimination based on animus, statistical discrimination, and cartel exploitation are analyzed for both race and sex discrimination. I explore the theoretical arguments for prohibiting private discriminatory conduct and illustrates the tensions that exist between concerns for liberty and equality. I also discuss the critical point that one cannot automatically attribute observed disparities in various economic or social outcomes to discrimination, and illustrate the complexities in establishing the existence of discrimination. The major empirical findings showing the effectiveness of federal law in the first decade after passage of the 1964 Civil Rights Act are contrasted with the generally less optimistic findings from subsequent antidiscrimination interventions.

Competition and Gender Prejudice: Are Discriminatory Employers Doomed to Fail?

According to Becker's (1957) famous theory on discrimination, entrepreneurs with a strong prejudice against female workers forgo profits by submitting to their tastes. In a competitive market their firms lack efficiency and are therefore forced to leave. We present new empirical evidence for this prediction by studying the survival of startup firms in a large longitudinal matched employer-employee data set from Austria. Our results show that firms with strong preferences for discrimination, i.e. a low share of female employees relatively to the industry average, have significantly shorter survival rates. This is especially relevant for firms starting out with female shares in the lower tail of the distribution. They exit about 18 months earlier than firms with a median share of females. We see no differences in survival between firms at the top of the female share distribution and at the median, though. We further document that highly discriminatory firms that manage to survive submit to market powers and increase their female workforce over time.firm survival, profitability, female employment, discrimination, market test, matched employer-employee data

The Evaluation of Immigrants' Credentials: The Roles of Accreditation, Immigrant Race, and Evaluator Biases

Theories of subtle prejudice imply that personnel decision makers might inadvertently discriminate against immigrant employees, in particular immigrant employees form racial minority groups. The argument is that the ambiguities that are associated with immigrant status (e.g., quality of foreign credentials) release latent biases against minorities. Hence, upon removal of these ambiguities (e.g., recognition of foreign credentials as equivalent to local credentials), discrimination against immigrant employees from minority groups should no longer occur. Experimental research largely confirmed these arguments, showing that participants evaluated the credentials of black immigrant employees less favorably only when the participants harbored latent racial biases and the foreign credentials of the applicants had not been accredited. The results suggest the importance of the official recognition of foreign credentials for the fair treatment of immigrant employees.Labour Discrimination, Immigrants, Racial Minorities, Prejudice, Credential Recognition, Experiment

Reducing violence and prejudice in a Jamaican all age school using attachment and mentalization theory

A study is reported of a psychoanalytic intervention in a very violent and prejudiced Jamaican school with disenfranchised children 7-9 grades who had failed academic streaming examinations. Over the period of 3 years of the intervention using mentalization and power issues approaches grounded in attachment theory, children were assisted to feel connected and valued by their school. There were striking improvements in academic performance, decreased victimization, and increased helpfulness especially in boys including significant trickle down effects to grades 1-6. Overall, the school became a place teachers wanted to join and the Jamaican government recognized their success and built a new school for them in a better location

Prognóstico de exploração no Chat GPT com ética de inteligência artificial

Natural language processing innovations in the past few decades have made it feasible to synthesis and comprehend coherent text in a variety of ways, turning theoretical techniques into practical implementations. Both report summarizing software and sectors like content writers have been significantly impacted by the extensive Language-model. A huge language model, however, could show evidence of social prejudice, giving moral as well as environmental hazards from negligence, according to observations. Therefore, it is necessary to develop comprehensive guidelines for responsible LLM (Large Language Models). Despite the fact that numerous empirical investigations show that sophisticated large language models has very few ethical difficulties, there isn't a thorough investigation and consumers study of the legality of present large language model use. We use a qualitative study method on OpenAI's ChatGPT3 to solution-focus the real-world ethical risks in current large language models in order to further guide ongoing efforts on responsibly constructing ethical large language models. We carefully review ChatGPT3 from the four perspectives of bias and robustness. According to our stated opinions, we objectively benchmark ChatGPT3 on a number of sample datasets. In this work, it was found that a substantial fraction of principled problems are not solved by the current benchmarks; therefore new case examples were provided to support this. Additionally discussed were the importance of the findings regarding ChatGPT3's AI ethics, potential problems in the future, and helpful design considerations for big language models. This study may provide some guidance for future investigations into and mitigation of the ethical risks offered by technology in large Language Models applications.Las innovaciones en el procesamiento del lenguaje natural en las últimas décadas han hecho posible sintetizar y comprender textos coherentes en una variedad de formas, transformando las técnicas teóricas en implementaciones prácticas. Ambos informan que el software extenso y las industrias como la de los creadores de contenido se han visto significativamente afectadas por el modelo de lenguaje extensivo. Sin embargo, un modelo de lenguaje enorme podría mostrar evidencia de sesgo social, dando riesgos morales y ambientales por negligencia, según las observaciones. Por lo tanto, es necesario desarrollar lineamientos completos para los LLM (Modelos de Lenguaje Grandes) responsables. A pesar de que numerosas investigaciones empíricas muestran que los modelos sofisticados de lenguaje amplio tienen muy pocas dificultades éticas, no existe una investigación exhaustiva y un estudio del consumidor sobre la legalidad del uso actual de modelos de lenguaje amplio. Usamos un método de estudio cualitativo en ChatGPT3 de OpenAI para enfocarnos en resolver los riesgos éticos del mundo real en los modelos actuales de lenguaje amplio para guiar aún más los esfuerzos en curso en la construcción responsable de modelos éticos de lenguaje amplio. Analizamos cuidadosamente ChatGPT3 desde las cuatro perspectivas de sesgo y robustez. De acuerdo con nuestras opiniones expresadas, comparamos ChatGPT3 objetivamente en múltiples conjuntos de datos de muestra. En este trabajo se encontró que una fracción sustancial de los problemas de principios no son resueltos por los marcos actuales; por lo tanto, se han proporcionado nuevos ejemplos de casos para respaldar esto. Además, se discutió la importancia de los hallazgos sobre la ética de la IA de ChatGPT3, los problemas potenciales en el futuro y las consideraciones de diseño útiles para modelos de lenguaje grandes. Este estudio puede proporcionar algunas pautas para futuras investigaciones y mitigación de los riesgos éticos que ofrece la tecnología en grandes aplicaciones de Language Models.As inovações de processamento de linguagem natural nas últimas décadas tornaram possível sintetizar e compreender textos coerentes de várias maneiras, transformando técnicas teóricas em implementações práticas. Ambos relatam que softwares resumidos e setores como criadores de conteúdo foram significativamente afetados pelo extenso modelo de linguagem. Um enorme modelo de linguagem, no entanto, poderia mostrar evidências de preconceito social, dando riscos morais e ambientais por negligência, de acordo com as observações. Portanto, é necessário desenvolver diretrizes abrangentes para LLM (Large Language Models) responsáveis. Apesar do fato de numerosas investigações empíricas mostrarem que modelos sofisticados de linguagem ampla têm muito poucas dificuldades éticas, não há uma investigação completa e estudo de consumidores sobre a legalidade do uso atual de modelos de linguagem ampla. Usamos um método de estudo qualitativo no ChatGPT3 da OpenAI para focar na solução os riscos éticos do mundo real nos atuais modelos de linguagem ampla, a fim de orientar ainda mais os esforços contínuos na construção responsável de modelos éticos de linguagem ampla. Analisamos cuidadosamente o ChatGPT3 a partir das quatro perspectivas de viés e robustez. De acordo com nossas opiniões declaradas, comparamos objetivamente o ChatGPT3 em vários conjuntos de dados de amostra. Neste trabalho, constatou-se que uma fração substancial dos problemas de princípios não é resolvida pelos referenciais atuais; portanto, novos exemplos de casos foram fornecidos para apoiar isso. Além disso, foram discutidas a importância das descobertas sobre a ética de IA do ChatGPT3, possíveis problemas no futuro e considerações de design úteis para grandes modelos de linguagem. Este estudo pode fornecer algumas orientações para futuras investigações e mitigação dos riscos éticos oferecidos pela tecnologia em grandes aplicações de Modelos de Linguagem

Corporal Punishment in Private Schools: The Case of Kathmandu, Nepal

The purpose of this study was to elaborate the situation of corporal punishment which is being practiced in Nepalese schools going against new policies that promote the non-violence teaching. It was based on original qualitative study of one private school of Kathmandu (the capital city of Nepal) having more than 2000 students and 100 teachers. Results from FGD, observation of the classroom practice, situational interviews with parents, teachers and students indicated that most teachers as well as parents thought, the best way to discipline children is punishment because it creates fear in them and this prevents misbehavior, promotes obedience and help to perform high academically. Teachers and administrators were found ignoring the rights of child and about the principles of child psychology and development.  Students had accepted the corporal punishment as a culture of school. This study is significant to know why teachers in private schools in Nepal often use the corporal punishment on students during teaching and learning periods. So this study is important for the government of Nepal, organization involving to child rights and stakeholders. The results showed the accepted and negated concept of social learning theory, power theory and choice theory by the parents, teachers, school principal and students. Keywords: Corporal punishment, Private school, Teachers, Parents, Students, Discipline, Violenc