---
title: "A Resource on Dialogical Moves in Native and Non-Native"
description: "It proposes a functional notion of academic nativeness: writers with English as their mother tongue or as a second language… 59 references."
authors: ["Giulia D'Agostino", "Narjes Sheikh Asadi", "Elena Musi"]
year: 2026
venue: "Proceedings of the Fifteenth Language Resources and Evaluation Conference"
source: "https://aclanthology.org/2026.lrec-1.502/"
doi: "10.63317/3cbozhs8zty6"
licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)"
licence_url: "https://creativecommons.org/licenses/by-nc/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/agostino-2026-resource-dialogical-moves-native-non/"
---
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# A Resource on Dialogical Moves in Native and Non-Native Academic Writers of English

**Authors:** Giulia D'Agostino, Narjes Sheikh Asadi and [Elena Musi](https://md.research.elamur.ai/free/en/authors/elena-musi/) · **Year:** 2026 · **Venue:** [Proceedings of the Fifteenth Language Resources and Evaluation Conference](https://md.research.elamur.ai/free/en/venues/lrec/) ([LREC 2026](https://md.research.elamur.ai/free/en/venues/lrec/2026/)) · **Publisher:** [European Language Resources Association (ELRA)](https://md.research.elamur.ai/free/en/publishers/european-language-resources-association-elra/) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.lrec-1.502/) · [PDF](https://aclanthology.org/2026.lrec-1.502.pdf) · [DOI 10.63317/3cbozhs8zty6](https://doi.org/10.63317/3cbozhs8zty6) · [OpenAlex](https://openalex.org/W7160200760)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
The paper argues that the usual native/non-native split, often guessed from author names and affiliations, fits academic English poorly. It proposes a functional notion of academic nativeness: writers with English as their mother tongue or as a second language used in daily life (L1 and ESL) count as "native." Writers who use English mainly for scientific communication (EFL) count as "non-native." The authors surveyed the authors of the articles they collected and used the self-assessments as ground truth for a binary classifier built on fine-tuned RoBERTa and DeBERTa. A retrieval-augmented RoBERTa variant performed best. They then release a corpus of 80 Linguistics research articles, labelled for academic nativeness, whose introductions are manually annotated for dialogical moves following Swales' CaRS model. Preliminary tests show that large language models still struggle to annotate these moves automatically. The features that separate academic natives from non-natives also differ from those usually reported for general native/non-native English. The resource targets academic writing pedagogy and computational discourse studies.

## Key points
- Corpus: 80 research articles from 16 Language/Linguistics journals, four per SJR quartile (Q1–Q4), with introductions annotated for CaRS moves: establishing a territory, identifying a gap, and occupying the niche.
- Survey: 114 authors were contacted through 278 personalised emails, and 52 gave valid answers. The classifier used 50 single-authored, open-access, English articles, with L1 and ESL merged into "native" and EFL as "non-native."
- Input: Abstract, Introduction, Discussion and Conclusion sections, split into sentences and regrouped into chunks of at most 128 tokens.
- Classification results (macro-F1): RAG+RoBERTa 0.94 (accuracy 0.95), RoBERTa 0.89, DeBERTa 0.84, RAG+DeBERTa 0.82. Retrieval helped RoBERTa but hurt DeBERTa.
- Setup: roberta-base and deberta-v3-base, 5-fold CV, only the top 4 layers trainable, class-weighted loss, AdamW, at most 10 epochs with early stopping on F1. Retrieval used all-MiniLM-L6-v2 to fetch 3 neighbours.

## Interesting ideas
- The authors replace a noisy proxy label (inferring nativeness from names) with labels the subjects report themselves, defined by how a person actually uses the language; this gives cleaner ground truth for a contested category.
- In retrieval-augmented fine-tuning, about 30% of inputs are deliberately left without retrieved neighbours, so the model cannot become dependent on retrieval at inference.
- On a tiny, noisy dataset, they freeze most of the encoder and tune only the top four layers, deliberately choosing small encoders over generative models to limit overfitting.
- Rhetorical moves (territory, gap, niche) are treated as functional units above the sentence, and the authors report that LLMs still find them hard to tag automatically.
- The journals were sampled evenly across quality quartiles rather than taken from top venues only, so contrasts are not confounded with venue prestige.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (learn): when building silver labels for fuzzy categories like register or text genre, prefer operational definitions tied to observable function over surface proxies, and document the definition next to the data.
- **I2** (learn): when the LLM-teacher or witness-parser pipeline feeds context examples into training, randomly withhold that context for a fraction of items so the student still works when retrieval fails.
- **I3** (tree): when adapting gparse to a small treebank or a new UD dialect, try partial unfreezing as a cheap guard against overfitting before full fine-tuning.
- **I4** (frames): a move layer could sit beside speech acts in prag, tagging sentences as background, gap claim or contribution from explicit cues; LLM-produced labels for it should be treated as unreliable without checks.
- **I5** (learn): stratify evaluation sets by source quality or difficulty bands so that score differences reflect the phenomenon being tested, not the mix of sources.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

📚 Shelves (3): [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 16,039 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 15,891 works · [📚 Literature and Literary Theory](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/literature-and-literary-theory/) · 519 works

🧭 Topics (1): [English](https://md.research.elamur.ai/free/en/topics/english/) · 2,263 works

## Cite

Cite as: Giulia D'Agostino, Narjes Sheikh Asadi and Elena Musi. 2026. A Resource on Dialogical Moves in Native and Non-Native Academic Writers of English. Proceedings of the Fifteenth Language Resources and Evaluation Conference.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{dagostino2026resource,
  title = {{A Resource on Dialogical Moves in Native and Non-Native Academic Writers of English}},
  author = {Giulia D'Agostino, Narjes Sheikh Asadi and Elena Musi},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
  year = {2026},
  doi = {10.63317/3cbozhs8zty6},
  url = {https://doi.org/10.63317/3cbozhs8zty6}
}
```

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## References

59 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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58. Hatice Çeşme and Oktay Yağız. 2020a. A Contrastive Rhetorical Analysis of Anglophone and Turkish Authors’ RA Introductions in ELT. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 24(2):899–915. [find](https://scholar.google.com/scholar?q=Hatice+%C3%87e%C5%9Fme+and+Oktay+Ya%C4%9F%C4%B1z%2E+2020a%2E+A+Contrastive+Rhetorical+Analysis+of+Anglophone+and+Turkish+Authors%E2%80%99+RA+Introductions+in+ELT%2E+Atat%C3%BCrk+%C3%9Cniversitesi+Sosyal+Bilimler+Enstit%C3%BCs%C3%BC+Dergisi%2C+24%282%29%3A899%E2%80%93915)
59. Hatice Çeşme and Oktay Yağız. 2020b. A contrastive rhetorical analysis of anglophone and turkish authors’ ra introductions in elt. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 24(2):899–915. [find](https://scholar.google.com/scholar?q=Hatice+%C3%87e%C5%9Fme+and+Oktay+Ya%C4%9F%C4%B1z%2E+2020b%2E+A+contrastive+rhetorical+analysis+of+anglophone+and+turkish+authors%E2%80%99+ra+introductions+in+elt%2E+Atat%C3%BCrk+%C3%9Cniversitesi+Sosyal+Bilimler+Enstit%C3%BCs%C3%BC+Dergisi%2C+24%282%29%3A899%E2%80%93915)

*Updated 1 November 2026*