The hottest Social Science Substack posts right now

And their main takeaways
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Top Science Topics

Two more random studies I found interesting

Samstack • 807 implied HN points • 14 Nov 23
🔬 Science Social Science Studies Discrimination Meta-analysis
  1. Support for right-wing parties may increase after right-wing terrorist attacks, contrary to previous evidence on political violence.
  2. Discrimination against women for jobs historically held by men has been non-existent since 2009, but there may still be bias in favor of female applicants.
  3. Meta-analyses, like the one discussed, offer valuable insights when designed carefully and with expert input to avoid bias.
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Why vaccine misinformation is winning the information war

Weaponized • 5 HN points • 17 Mar 24
🏥 Health & Wellness Misinformation Vaccines Communication Trust Social Science
  1. Misinformation about vaccines is spreading faster than efforts to debunk it, limiting the impact of accurate information campaigns.
  2. Addressing vaccine misinformation needs to consider the complex reasons why people fall for it, such as political beliefs or past mistreatment by authorities.
  3. Combatting vaccine misinformation requires more than just sharing facts, it's crucial to understand the root causes of hesitancy and engage with empathy and trust.

Against the Labor Theory of Science

Never Met a Science • 11 implied HN points • 23 Jan 24
🔬 Science Social Science Theory Machine Learning
  1. New social scientific processes are being developed for more efficiency and improved knowledge production.
  2. Centralization of knowledge production can lead to significant gains in efficiency on both production and consumption sides.
  3. Machine learning algorithms can extract high-dimensional knowledge, reducing the need for human translation and potentially improving accuracy.

SociaLLM: proposal for a language model design for personalised apps, social science, and AI safety research

Engineering Ideas • 19 implied HN points • 19 Dec 23
🕹 Technology AI Social Science Research Applications Training
  1. SociaLLM is a foundation language model trained on chat, dialogue, and forum data with stable message authors and timestamps.
  2. Industrial applications of SociaLLM include personalized content recommendations, customer service, education, and mental health support.
  3. SociaLLM has research and AI safety applications in social science, collective intelligence, and studying mechanisms to prevent deception and collusion in AI.

The hubris of social scientists

Hypertext • 0 implied HN points • 27 Mar 24
🔬 Science Social Science Public Policy
  1. Researchers should expand beyond randomized trials in social science evaluations due to the complexity of the social world and challenges in replicating findings.
  2. The 'hubris of social scientists' refers to the overconfidence and limitations in assuming new ideas will succeed, highlighting the commonality of failures in various fields, not just social policy.
  3. Identifying small effects in social science research is difficult due to the high variability across contexts, limitations in sample sizes, and challenges in replicating studies, necessitating a more systematic approach to data collection and policy evaluation.

Causal research: More, not less

Hypertext • 0 implied HN points • 27 Mar 24
🚌 Education Research Policy Social Science Evidence Public Policy
  1. Understanding the effects of policies on people's lives is crucial, and causal research can provide valuable information to guide decision-making.
  2. Critiques of causal social science highlight the need for improvement in research publishing practices, such as publishing null studies and ensuring clarity on statistically significant but small results.
  3. Replication studies in policy-making, especially with experimental interventions like RCTs, can offer valuable insights to refine policies before widespread implementation, and continuous use of evidence can help in making incremental progress.

Issue index

Hypertext • 0 implied HN points • 27 Mar 24
🇺🇸 U.S. Politics Research Policy Government Data Social Science
  1. The post contains 19 essays focusing on various important topics like research, policy, and social science.
  2. The essays discuss the importance of evidence-based decision-making and the challenges faced in implementing change.
  3. Authors explore subjects such as research integrity, government transparency, and the complexities of driving societal change.

The world is hard to change

Hypertext • 0 implied HN points • 27 Mar 24
🇺🇸 U.S. Politics Policy Social Science Political Science
  1. Social science has its limits when it comes to creating large, lasting changes through evidence-based policymaking.
  2. Social science is about learning from failures and adapting to the challenges of understanding and changing human behavior.
  3. Disappointment in evidence-based policymaking does not justify reverting to ideological assumptions; instead, it highlights the complexity of creating effective social change.

Incrementalism beats YOLO

Hypertext • 0 implied HN points • 27 Mar 24
🇺🇸 U.S. Politics Policy Social Science Interventions Research
  1. Incremental social policies have proven to make the world a better place over time
  2. Narrow, incremental policy changes can have significant positive impacts, like increasing school attendance, boosting earnings, and reducing incarceration rates
  3. Incremental changes informed by high-quality evaluation and research can lead to greater effectiveness over time in various social programs, showing better results than 'you only live once' approaches in policy-making

Data in, garbage out

Hypertext • 0 implied HN points • 27 Mar 24
🔬 Science Data Analysis Social Science Interventions
  1. Statistics can only tell us so much, so we should approach data with humility about both the power of social programs and hard data to test them.
  2. Rigorous measurement often doesn't definitively show whether interventions work, leading to ongoing debates and conflicting results in various fields.
  3. While randomized controlled trials have their value in measuring specified outcomes, they can miss unexpected effects and subtle interactions, highlighting the importance of qualitative methods and personal observations.