# Research Borderlands: Analysing Writing Across Research Cultures

arXiv: https://arxiv.org/abs/2506.00784 · HTML: https://mlsanity.com/paper/2506.00784/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 33 of its 64 references that are in the map.
- First posted on arXiv 1 Jun 2025.

## Builds on (most cited first, 30 of 33)

- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
- [Language (Technology) is Power: A Critical Survey of "Bias" in NLP](https://mlsanity.com/paper/2005.14050/) (2020)
- [Agent Laboratory: Using LLM Agents as Research Assistants](https://mlsanity.com/paper/2501.04227/) (2025)
- [Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers](https://mlsanity.com/paper/2409.04109/) (2024)
- [Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer](https://mlsanity.com/paper/1803.06535/) (2018)
- [The Values Encoded in Machine Learning Research](https://mlsanity.com/paper/2106.15590/) (2021)
- [Towards Measuring and Modeling "Culture" in LLMs: A Survey](https://mlsanity.com/paper/2403.15412/) (2024)
- [Mapping the Increasing Use of LLMs in Scientific Papers](https://mlsanity.com/paper/2404.01268/) (2024)
- [Re-imagining Algorithmic Fairness in India and Beyond](https://mlsanity.com/paper/2101.09995/) (2021)
- [Survey of Cultural Awareness in Language Models: Text and Beyond](https://mlsanity.com/paper/2411.00860/) (2024)
- [The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text](https://mlsanity.com/paper/2311.09807/) (2023)
- [The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice](https://mlsanity.com/paper/2310.00907/) (2023)
- [Re-contextualizing Fairness in NLP: The Case of India](https://mlsanity.com/paper/2209.12226/) (2022)
- [Echoes in AI: Quantifying lack of plot diversity in LLM outputs](https://mlsanity.com/paper/2501.00273/) (2024)
- [LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions](https://mlsanity.com/paper/2411.05025/) (2024)
- [Detection and Measurement of Syntactic Templates in Generated Text](https://mlsanity.com/paper/2407.00211/) (2024)
- [AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text](https://mlsanity.com/paper/2410.04265/) (2024)
- [Culture is Not Trivia: Sociocultural Theory for Cultural NLP](https://mlsanity.com/paper/2502.12057/) (2025)
- [Data-driven Discovery with Large Generative Models](https://mlsanity.com/paper/2402.13610/) (2024)
- [What Do NLP Researchers Believe? Results of the NLP Community Metasurvey](https://mlsanity.com/paper/2208.12852/) (2022)
- [Scim: Intelligent Skimming Support for Scientific Papers](https://mlsanity.com/paper/2205.04561/) (2022)
- [Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness](https://mlsanity.com/paper/2303.17555/) (2023)
- [Extrinsic Evaluation of Cultural Competence in Large Language Models](https://mlsanity.com/paper/2406.11565/) (2024)
- [Community Identity and User Engagement in a Multi-Community Landscape](https://mlsanity.com/paper/1705.09665/) (2017)
- [The Case for "Thick Evaluations" of Cultural Representation in AI](https://mlsanity.com/paper/2503.19075/) (2025)
- [Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publications](https://mlsanity.com/paper/2212.09676/) (2022)
- [Detecting Text Formality: A Study of Text Classification Approaches](https://mlsanity.com/paper/2204.08975/) (2022)
- [Interdisciplinarity as Diversity in Citation Patterns among Journals: Rao-Stirling Diversity, Relative Variety, and the Gini coefficient](https://mlsanity.com/paper/1807.04115/) (2018)
- ["You Cannot Sound Like GPT": Signs of language discrimination and resistance in computer science publishing](https://mlsanity.com/paper/2505.08127/) (2025)
- [Understanding "Democratization" in NLP and ML Research](https://mlsanity.com/paper/2406.11598/) (2024)

## Built on by (most cited first, 3 of 3)

- [TALES: A Taxonomy and Analysis of Cultural Representations in LLM-generated Stories](https://mlsanity.com/paper/2511.21322/) (2025)
- [Characterizing Cultural Localization in AI-Generated Stories](https://mlsanity.com/paper/2606.14626/) (2026)
- [CultureMINE: Datasets and Methods for Improving the Cultural Capabilities of NLP Systems](https://mlsanity.com/paper/2609.22494/) (2026)

## Abstract (arXiv)

Improving cultural competence of language technologies is important. However most recent works rarely engage with the communities they study, and instead rely on synthetic setups and imperfect proxies of culture. In this work, we take a human-centered approach to discover and measure language-based cultural norms, and cultural competence of LLMs. We focus on a single kind of culture, research cultures, and a single task, adapting writing across research cultures. Through a set of interviews with interdisciplinary researchers, who are experts at moving between cultures, we create a framework of structural, stylistic, rhetorical, and citational norms that vary across research cultures. We operationalise these features with a suite of computational metrics and use them for (a) surfacing latent cultural norms in human-written research papers at scale; and (b) highlighting the lack of cultural competence of LLMs, and their tendency to homogenise writing. Overall, our work illustrates the efficacy of a human-centered approach to measuring cultural norms in human-written and LLM-generated texts.