---
title: "English across Borders — paper by Sheeraz (2022)"
description: "The study asks whether English in Pakistan, India and Bangladesh, three former parts of British India now divided by political borders, has… 36 references."
authors: ["M. Ali, M. Sheeraz"]
year: 2022
venue: "NUML Journal of Critical Inquiry 19"
source: "https://jci.numl.edu.pk/index.php/jci/article/view/205"
doi: "10.52015/numljci.v19iii.205"
licence: "CC BY-NC (journal licence per DOAJ; NUML Journal of Critical Inquiry)"
licence_url: "https://creativecommons.org/licenses/by-nc/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/ali-2022-english-across-borders-exploring-register/"
---
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# English across Borders: Exploring Register Variation in South Asian Newspaper Editorials

**Authors:** M. Ali, M. Sheeraz · **Year:** 2022 · **Venue:** NUML Journal of Critical Inquiry 19 · **Licence:** [CC BY-NC (journal licence per DOAJ; NUML Journal of Critical Inquiry)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://doi.org/10.52015/numljci.v19iii.205) · [PDF](https://jci.numl.edu.pk/index.php/jci/article/download/205/73) · [DOI 10.52015/numljci.v19iii.205](https://doi.org/10.52015/numljci.v19iii.205) · [OpenAlex](https://openalex.org/W4220846741)

**Citations:** 1 citations (OpenAlex, 2026-10-14)

## Summary
The study asks whether English in Pakistan, India and Bangladesh, three former parts of British India now divided by political borders, has developed distinct written norms in one register: newspaper editorials. The authors built a balanced corpus of 288 editorials, published May 2020 to May 2021. It covers three widely read newspapers each from Pakistan, India, Bangladesh and Britain, with Britain serving as the reference variety. The texts were processed with Biber's tagger, and feature frequencies were normalized and standardized as z-scores. They were then combined into scores on Biber's (1988) five textual dimensions, and ANOVA was used to compare the four groups. Pakistani editorials came out as the most informational and the most abstract. Indian editorials were the least abstract, and Bangladeshi editorials were the most explicit and argumentative but the least informational. British editorials scored lowest on argumentation and explicitness. The authors conclude that each South Asian variety differs from British usage and also from its neighbours. In their view, folding them all under the label "Indian English" hides real variation.

## Key points
- Corpus: 12 newspapers, 3 per country, with 24 editorials per paper and 72 per country, totalling 288 texts. Sources include Dawn, The News International, Pakistan Observer, The Times of India, The Indian Express, The Telegraph, The Daily Star, Daily Sun, The Independent, The Guardian, The Sunday Times and Morning Star.
- Biber's tagger marked 150+ lexico-grammatical features per text. A dimension score is the sum of standardized frequencies of features loading positively, minus those loading negatively.
- Dimension 1 (Involved vs. Informational): all four groups are strongly informational. Pakistan is lowest (most informational) at about −15.96 and Bangladesh highest at about −13.16.
- Dimension 5 (Abstract/Impersonal): Pakistan 3.71, Bangladesh 2.82, Britain 1.63, India 1.04. Following Biber (1988), this dimension has no negatively loading features.
- Bangladeshi editorials stand out on argumentation through suasive verbs like "should", necessity modals and infinitives. On Dimension 2 their score sits near zero, which the authors read as mixed narrative/non-narrative purpose.

## Interesting ideas
- Register is described through bundles of co-occurring features rather than any single marker, which gives a more stable and generalizable profile of a text type.
- Each dimension score is a transparent signed sum of z-scored feature rates, so every score can be traced back to the exact features that produced it.
- Suasive verbs, necessity modals and infinitives are treated as surface signals of persuasive, argumentative stance.
- Heavy use of passives, especially agentless ones, is read as demoting or hiding the doer, which makes the text impersonal.
- The corpus design holds the register fixed and balances sources and time span, so differences can be attributed to variety rather than topic or sampling.

## For Mova

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

- **I1** (tokens): The tagger's morphological and POS output could feed a small register profiler, so later stages know whether they face argumentative, narrative or informational prose.
- **I2** (learn): Evaluation reports could use this signed-sum style to explain why a text or corpus slice behaves differently, rather than relying on opaque embeddings.
- **I3** (frames): The speech-act layer in prag could use the density of these markers as evidence for directive or advisory acts at the paragraph level.
- **I4** (world): When a text is passive-dense, the world builder should flag events with unknown or demoted agents explicitly instead of guessing who acted.
- **I5** (learn): Treebank and silver-data audits could use the same balanced, matched-register design when testing whether parsers degrade on South Asian or other non-British English.

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

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## Cite

Cite as: M. Ali, M. Sheeraz. 2022. English across Borders: Exploring Register Variation in South Asian Newspaper Editorials. NUML Journal of Critical Inquiry 19.

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

```bibtex
@article{sheeraz2022english,
  title = {{English across Borders: Exploring Register Variation in South Asian Newspaper Editorials}},
  author = {M. Ali, M. Sheeraz},
  journal = {NUML Journal of Critical Inquiry 19},
  year = {2022},
  doi = {10.52015/numljci.v19iii.205},
  url = {https://doi.org/10.52015/numljci.v19iii.205}
}
```

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## References

36 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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*Updated 24 October 2026*