52442 research outputs found
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Intersectional patterns in higher education STEMM: The role of gender, ethnicity and parental transmission
No full textExploring intersectional inequalities in students' sense of belonging in education across educational pathways and across educational contexts
No full textPerplexity-inspired metasearch-based alternatives to FAIR GPT: Open-source AI consultants for research data management
No full textChatbots and virtual assistants are becoming increasingly popular for user questions and support. With FAIR GPT, the Mannheim University Library released a virtual assistant for research data management (RDM) in 2024, designed to help researchers and institutions in making their data FAIR (Findable, Accessible, Interoperable, Reusable). FAIR GPT provides various RDM services, e.g. metadata enhancement, repository selection and FAIR assessment. However, FAIR GPT has numerous disadvantages: As a ‘Custom GPT’ of OpenAI, it is proprietary software that only outputs sources for the generated answers if it uses its internal web search tool (which cannot be controlled by the user) and therefore lacks transparency. Reliance on external cloud-based services leads to privacy concerns when dealing with sensitive (meta)data and the chatbot is still prone to hallucinations, thus reducing its trustworthiness. These issues led us to explore alternative open-source solutions. We searched for opensource alternatives to Perplexity.ai, a system known for its ability to provide citations for the information it retrieves through web searches. We identified three candidates available on GitHub: Perplexica, sensei, and farfalle. These tools use local instances of the metasearch engine SearXNG to perform internet searches, using the results as input for Large Language Models (LLMs). We modified these tools to focus specifically on RDM tasks, releasing the new versions on GitHub openly under the names FAIRplexica, FAIR-sensei and FAIR-farfalle
Noch immer wirtschaftlich neutral? Die Wirtschaftsverfassung des "ökologisch scharfgestellten" Grundgesetzes
No full textIssue congruence between candidates' Twitter communication and constituencies in an MMES: Migration as an exemplary case
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Cheap energy at what cost? The economic case for eliminating fossil fuel subsidies
No full textMany governments still help to keep fossil fuels cheap – sometimes by directly paying part of the supply cost (explicit subsidies), and at other times by not including the hidden costs of pollution and health problems they cause in their price (implicit subsidies). But what is the true cost to us? Would it be a good idea for countries to discontinue these subsidies and ensure that fossil fuel prices reflect the full impact of using these energies? And to what extent would this help countries to achieve their climate targets under the Paris Agreement? We study these questions across a broad range of countries by combining economic modelling with detailed data on fossil fuel subsidies, external costs of fossil fuels and national income and product accounts. We find that a unilateral elimination of explicit and implicit subsidies on fossil fuels would improve public finances in most countries, raise more fiscal revenues for governments and considerably reduce CO2 emissions. About one third of countries would already meet their climate targets in this scenario, making additional policies like carbon pricing redundant. Eliminating all direct fossil fuel subsidies worldwide would have only a limited effect in curbing global emissions. However, addressing the hidden costs of fossil fuel use – by “getting energy prices right” – could reduce global carbon emissions by one third, while simultaneously increasing both global and country-level welfare. Our findings highlight that economic, fiscal and climate targets can, in principle, be aligned
Intergenerational mobility in Latin America: The multiple facets of social status and the role mothers
No full textWe assess intergenerational mobility in terms of education and income rank in five Latin American countries—Brazil, Chile, Ecuador, Mexico, and Panama—by accounting for the education and occupation of both parents. Based on the Lubotsky and Wittenberg (2006) approach, we find that intergenerational persistence estimates increase by 26% to 50% when parents’ occupations are considered alongside their education to proxy family socioeconomic background. The increase is particularly strong when education is more evenly distributed in the parents’ generation. Furthermore, we assess how the informativeness of each proxy for parental background evolves across countries and over time, and find that maternal characteristics have become increasingly informative in recent decades, in line with rising women’s educational attainment and labor force participation. Interesting heterogeneities across countries and cohorts are observe
