Laura K. Nelson

@lauraknelson.bsky.social

Associate Professor @ UBC computational sociology machine learning is feminist You only have to look at the Medusa straight on to see her. And she’s not deadly. She’s beautiful and she’s laughing. www.lauraknelson.com

Who's up for a good old fashioned (but short, bc I'm tired) paper thread? Thrilled to be in this special issue of Gender & Society (an absolute dream!), where we propose a feminist-inspired extension of how to theorize and model the spread of ideas in science + journals.sagepub.com/doi/10.1177/...

What Gets Lost in Translation? Epistemic Tensions between Translation and Diffusion in Practice-Oriented Scholarship

Abstract
This paper proposes a feminist-informed metascience theory to explain the interconnected processes of idea creation, translation, and diffusion. Drawing on feminist critiques of science centered on perspective, power, and praxis, we develop a creation–diffusion model that jointly examines how ideas are created and then how the content of ideas influences their spread across academic fields. Using a nationally funded gender equity program as a case of a practice-oriented knowledge-production community, we analyze how gender equity research concepts were translated and diffused through the program-funded publications. We operationalize substantive engagement with gender equity research using word embeddings and Concept Mover’s Distance. Then, with additional contextual variables, we measure (1) the predictors of this engagement (ideas) and (2) the impact of engagement on citation counts and citation interdisciplinarity (the diffusion process) across social science and STEM fields. Our findings show that, in addition to context, the content of the idea matters for diffusion: Engagement with critical dimensions of gender equity research, such as feminism and structural concepts, diffused less often, whereas other dimensions, such as gender and methods, achieved broader uptake. Our empirical findings highlight the role of perspectives and epistemic power in shaping both knowledge production and diffusion. Our theoretical framework and methods demonstrate how metascience can incorporate feminist theory directly into diffusion studies, and why it should.
Mark Rubin@markrubin.bsky.social · 2w ago

Introduction to a special issue on feminist metascience and open science by Christin Munsch and @divreyes.bsky.social doi.org/10.1177/0891...

Abstract This introduction brings feminist scholarship into conversation with metascience and open science. Drawing on feminist epistemology, we argue scientific reform is not a neutral technical project. Rather, practices intended to improve rigor, transparency, and accessibility may also expose marginalized scholars and research participants to harm, reproduce inequality, and facilitate hostile scrutiny, particularly in the current political environment. These tensions point to the need for feminist metascience and feminist open science. We define feminist metascience as the study of how gender and intersecting relations of power shape the production, evaluation, circulation, and correction of scientific knowledge, and we define feminist open science as an approach to transparency that remains attentive to care, protection, and risk. We offer these definitions and the articles in this special issue as a starting point for larger conversations about how feminist scholarship might contribute to emerging debates over scientific reform.

This topic is on fire rn, but this is correct. And for those concerned with bias, here's the thing: you can intentionally push AI-based search around in ways you can't possibly do with web search. If you want more minority voices in your search results, AI search is far, far superior to web search.

【randi】@dopamine.church · 5d ago

i just cant take anyone that preaches web search is superior to AI seriously. web search is great - except for the seo manipulation, ads, and lack of weighting of sources, which would be a very difficult task to do even if it wasn't mangled by late stage capitalism and the current political climate.

I've been maintaining a thread of AI artworks by women artists because someone made a post about how women don't use AI because they have more tech literacy and I was like that completely ignores so much great work being done by women

A frustrating pattern in news coverage of AI (etc.) in soc sci & humanities: articles that focus on those critical of AI often quote women (and they should! it's great work!), but when it's about AI as a (serious) method, no/few women quoted. Maybe don't repeat patterns of the past this time? 🙏

We have re-opened our search for a 3-year AI-research postdoc at NYU's Center for Social Media, AI, and Politics!! The position starts this **September 1st** (or as soon as possible thereafter) and is in person at NYU. If necessary, we will also consider a 1/1/27 start. 1/3

The free version of ChatGPT automatically searches the web. The prompt "What are the most relevant sources for the claim that LLMs hallucinate?" returns the following. All those link buttons in the output are live hyperlinks that were found, not generated. If this isn't a search engine, what is it?

The foundational paper (introduced the term in the LLM context)
Ji et al. (2023)

Ji, Ziwei, et al. “Survey of Hallucination in Natural Language Generation.” ACM Computing Surveys 55, no. 12 (2023): 248.

This is the standard survey article.

It defines hallucination as generated content that is nonsensical or unfaithful to the provided source/input.

It distinguishes intrinsic hallucinations (contradict the source) from extrinsic hallucinations (unsupported by the source).

Useful when you need a general definition and overview of causes, detection, and mitigation strategies.

The paper most often cited for why hallucinations occur
Maynez et al. (2020)

Maynez, Joshua, et al. “On Faithfulness and Factuality in Abstractive Summarization.” Proceedings of ACL (2020).

Shows that neural generation systems often produce statements that are not supported by the source text.

Helped establish factuality/faithfulness as a core evaluation problem for generative models.

Frequently cited as evidence that hallucination is not an edge case but a structural property of neural text generation.

The key benchmark paper
TruthfulQA

Lin, Stephanie, Jacob Hilton, and Owain Evans. “TruthfulQA: Measuring How Models Mimic Human Falsehoods.” ACL (2022).

Evaluates whether models give truthful answers to questions that commonly elicit misconceptions.

Larger models often performed worse on truthfulness than smaller ones, because they better imitate patterns in web text.

This is one of the strongest empirical demonstrations that scaling alone does not eliminate hallucinations.

The classic “stochastic parrots” critique
Bender et al. (2021)

Bender, Emily M., et al. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” FAccT (2021).

Does not use the term “hallucination” as the central concept.
...
Laura K. Nelson@lauraknelson.bsky.social · 3w ago

I'm once again begging everyone to update their priors. "ChatGPT is not a search engine." Yes, yes it is. It actively searches the web based on your prompt, and returns active links relevant to your search/prompt. It's a search engine. It is. (Obvs don't use it that way if that's not your thing)

I'm once again begging everyone to update their priors. "ChatGPT is not a search engine." Yes, yes it is. It actively searches the web based on your prompt, and returns active links relevant to your search/prompt. It's a search engine. It is. (Obvs don't use it that way if that's not your thing)

This bot's description of the chart it's responding to is *chef's kiss* (The chart in fact shows the opposite: the final grades were much lower, even as numerous midterm grades hit 100. Almost certainly because of AI use on the midterm.)

SScribe@bskyscribe.bsky.social · 4w ago

A bar chart titled 'ECON 1170 Midterm & Final Scores' shows midterm (orange) and final exam (gray) scores for 59 students. Many students improved significantly from midterm to final, with numerous final scores hitting 100, even for those with low midterm scores.

I want my fellow sociologists (&related) to see this and really understand what's happening. This is just one of many this size. When a university says "we're hiring 100 faculty in AI" and your response is to scoff, are there even 100 people who could fill those positions? Yes. There are thousands.

Jacob Eisenstein@jacobeisenstein.bsky.social · 4w ago

a spontaneously-formed triple snaking queue to enter the #icml2026 poster session. the conference sold out before the early bird registration period ended. no shade whatsoever to the organizers, who are making the best of this, but we have strayed from light. conferences cannot be this big.