"Call me sexist, but...": Revisiting Sexism Detection Using Psychological Scales and Adversarial Samples

Research has focused on automated methods to effectively detect sexism online. Although overt sexism seems easy to spot, its subtle forms and manifold expressions are not. In this paper, we outline the different dimensions of sexism by grounding them in their implementation in psychological scales. From the scales, we derive a codebook for sexism in social media, which we use to annotate existing and novel datasets, surfacing their limitations in breadth and validity with respect to the construct of sexism. Next, we leverage the annotated datasets to generate adversarial examples, and test the reliability of sexism detection methods. Results indicate that current machine learning models pick up on a very narrow set of linguistic markers of sexism and do not generalize well to out-of-domain examples. Yet, including diverse data and adversarial examples at training time results in models that generalize better and that are more robust to artifacts of data collection. By providing a scale-based codebook and insights regarding the shortcomings of the state-of-the-art, we hope to contribute to the development of better and broader models for sexism detection, including reflections on theory-driven approaches to data collection.Comment: Indira Sen and Julian Kohne contributed equally to this wor

People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection

NLP models are used in a variety of critical social computing tasks, such as detecting sexist, racist, or otherwise hateful content. Therefore, it is imperative that these models are robust to spurious features. Past work has attempted to tackle such spurious features using training data augmentation, including Counterfactually Augmented Data (CADs). CADs introduce minimal changes to existing training data points and flip their labels; training on them may reduce model dependency on spurious features. However, manually generating CADs can be time-consuming and expensive. Hence in this work, we assess if this task can be automated using generative NLP models. We automatically generate CADs using Polyjuice, ChatGPT, and Flan-T5, and evaluate their usefulness in improving model robustness compared to manually-generated CADs. By testing both model performance on multiple out-of-domain test sets and individual data point efficacy, our results show that while manual CADs are still the most effective, CADs generated by ChatGPT come a close second. One key reason for the lower performance of automated methods is that the changes they introduce are often insufficient to flip the original label.Comment: Preprint of EMNLP'23 pape

Electoral Uncertainty, Income Inequality and the Middle Class

We investigate how electoral competition affects the income distribution in society. We utilise a standard probabilistic voting setup where parties compete at two stages. Our model delivers that greater electoral competition in a district results in equalisation of incomes therein. We check for these relationships using data from Indian national elections which are combined with consumption expenditure data rounds from the National Sample Survey Organization (1987–8 and 2004–5) to yield a district level panel. Our OLS, 2-SLS and IIV analyses consistently inform that close elections lead to lower inequality and polarisation indicating a larger middle class

Gender-Responsive Budgeting as Fiscal Innovation: Evidence from India on 'Processes'

Gender-responsive budgeting (GRB) is a fiscal innovation. Innovation, for the purposes of this paper, is defined as a way of transforming a new concept into tangible processes, resources, and institutional mechanisms in which a benefit meets identified problems. GRB is a fiscal innovation in that it translates gender commitments into fiscal commitments by applying a "gender lens" to the identified processes, resources, and institutional mechanisms, and arrives at a desirable benefit incidence. The theoretical treatment of gender budgeting as a fiscal innovation is not incorporated, as the focus of this paper is broadly on the processes involved. GRB as an innovation has four specific components: knowledge processes and networking, institutional mechanisms, learning processes and building capacities, and public accountability and benefit incidence. The paper analyzes these four components of GRB in the context of India. The National Institute of Public Finance and Policy has been the pioneer of gender budgeting in India, and also played a significant role in institutionalizing gender budgeting within the Ministry of Finance, Government of India, in 2005. The Expert Committee Group on "Classification of Budgetary Transactions" makes recommendations on gender budgeting - Ashok Lahiri Committee recommendations - that will become part of the institutionalization process, integrating the analytical matrices of fiscal data through a gender lens and also the institutional innovations for GRB. Revisiting the 2004 Lahiri recommendations and revamping the process of GRB in India is inevitable, at both ex ante and ex post levels

Serum brain-derived neurotrophic factor: Determinants and relationship with depressive symptoms in a community population of middle-aged and elderly people

OBJECTIVES: Brain-derived neurotrophic factor (BDNF) is involved in major depressive disorder and neurodegenerative diseases. Clinical studies, showing decreased serum BDNF levels, are difficult to interpret due to limited knowledge of potential confounders and mixed results for age and sex effects. We explored potential determinants of serum BDNF levels in a community sample of 1230 subjects. METHODS: Multiple linear regression analyses with serum BDNF level as the dependent variable were conducted to explore the effect of four categories of potential BDNF determinants (sampling characteristics, sociodemographic variables, lifestyle factors and somatic diseases) and of self-reported depressive symptoms (Beck's Depression Inventory (BDI). RESULTS: Our results show that BDNF levels decline with age in women, whereas in men levels remain stable. Moreover, after controlling for age and gender, the assays still showed lower serum BDNF levels with higher BDI sum scores. Effects remained significant after correction for two main confounders (time of sampling and smoking), suggesting that they serve as molecular trait factors independent of lifestyle factors. CONCLUSIONS: Given the age-sex interaction on serum BDNF levels and the known association between BDNF and gonadal hormones, research is warranted to delineate the effects of the latter interaction on the risk of psychiatric and neurodegenerative diseases

Bycatch in Indian trawl fisheries and some suggestions for trawl bycatch mitigation

Globally, trawl is the major fishing gear used in marine fisheries and in India, it contributes to more than onethird of the marine fish production. Trawl fishing has been critically evaluated from a sustainability perspective, especially analysing its bycatch composition. Most of the bycatch from trawlers contains valuable edible species with high market demand. However, a portion of the bycatch which does not have such demand in the edible fish market, known as low-value bycatch (LVB), continues to be a matter of concern from an ecological and economic perspective. During 2017–19, 30–60% of trawl landing in India was constituted by LVB, which was mainly used for fishmeal preparation. To enhance the value and utility of LVB, this study explores the possibility of converting waste from LVB into edible resources using pufferfish and triggerfish. It also highlights the positive impact of efforts by different Government agencies for bycatch mitigation like the implementation of minimum legal size in reducing the juvenile component in bycatch, with a social survey-based account of fisher’s perceptions and suggestions on successful bycatch mitigation

Religion and human relationships in E. M. Forster's <A passage to India<

This thesis examines E.M.Forster's dealings with religions in his most famous novel A Passage to India. Forster as a realistic writer, was deeply interested in human relationships and in A Passage to India , he tried to examine this issue from a religious point of view. Although here religions refer generally to Islam, Christianity and Hinduism, my interest mainly lies in Hinduism. This Hinduism is displayed here through the "Krishna-festival," and the main focus of my thesis will be on this festival. Bearing this in mind, I will try to show that Forster brought religion into literature to secure a place for mankind. Here the appealing image of a Hindu festival will be discussed in relation to its function of establishing human relationships. Religion here means realisation of some higher values and practical expression to the divinity, which help human beings to endure all kinds of sufferings in life. The evaluation of the role of religion to establish human relationships is, however, the main point of the thesis. It will examine the role of religion to eliminate the conflicts of life and also show how religion offers some hope for temporary reconciliation