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Postcolonial Literature and World Englishes: A Corpus-Based Approach of Modes of Representation of the Non-Standard in Writing

Paper · 2017 · Michael Percillier and Catherine Paulin

Summary

The paper asks how writers render non-standard Englishes in prose fiction, and how closely those renderings match the real varieties. The authors built a literary corpus from anthologies and collections. It has an Outer Circle part (West Africa, Southeast Asia) and an Inner Circle reference part (Scotland). They hand-annotated it in XML for non-standard features in four categories: phonology, grammar, lexis and code. They also marked which character or narrator is speaking. Cross-regional comparisons use normalised frequencies, and grammatical features are linked to eWAVE so their spread in literature can be set against eWAVE's frequency ratings for the real varieties.

Each region leans on one dominant category: Scottish texts on phonological respellings, Southeast Asian texts on code-mixing, West African texts on grammar. Scottish texts are also far denser in non-standard features. Within texts, feature choices signal a character's social status, ethnicity and age. The accuracy check shows that authors often skip frequent but widely shared features. Instead they use rarer but emblematic ones, or even features not attested in the variety. This suggests literary dialect is more symbolic than mimetic.

Key points

  • The corpus has three sub-corpora:
    • West Africa: 60,704 words, from Nigeria and Sierra Leone.
    • Southeast Asia: 75,588 words, from Singapore, Malaysia and the Philippines.
    • Scotland: 21,269 words.
    • The target is about 100,000 words per sub-corpus, balanced by decade.
  • The XML annotation records the feature category, the observed form and the expected standard form. Depending on the category, it can also record meaning, language and an eWAVE feature ID.
  • The "phonology" category only covers respellings that change pronunciation (e.g. de for the). Respellings that leave the sound unchanged ("eye-dialect", e.g. lissen) are kept out of it.
  • Measured per 10,000 words, Scottish texts have about eight times the density of non-standard features found in West African texts, and the West African texts are themselves denser than the Southeast Asian ones.
  • Scottish texts show only one eWAVE A-rated (pervasive) grammatical feature, and it appears in just half the texts.
    • Quotative like is rated pervasive for Scottish English but never occurs in the Scottish texts.
    • The B-rated past-tense levelling (telt for told) appears in five of eight texts.

Interesting ideas

  • I1. Each non-standard token is annotated with both the observed form and its standard counterpart, so variation is stored as an explicit mapping rather than as noise.
  • I2. Respellings that change pronunciation are separated from purely visual "eye-dialect" ones, because only the former carry linguistic information.
  • I3. Non-standard features are attributed to specific characters or the narrator, so density and feature type can be read as part of a character profile (status, ethnicity, age).
  • I4. Observed feature frequencies are compared with an external reference grading (eWAVE A/B/D/X), which exposes both omitted frequent features and unattested "invented" ones.
  • I5. The finding that writers favour emblematic features over frequent but widely shared ones ("iconicity trumps frequency") warns against treating fiction as a faithful sample of real speech.

For Mova

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

  • I1 (tokens): The en tokenizer and lemmatizer could keep a standard-equivalent field for dialectal or respelled tokens (e.g. telt → told, de → the), so later stages work on normalised forms while the original surface form stays traceable.
  • I2 (tokens): Normalisation rules could flag whether a respelling is phonological or cosmetic, which lets dialogue in fiction be normalised without losing signals about how a character speaks.
  • I3 (world): Entities in the text world could carry a speech-style profile built from the dialect features in their quoted lines, which would help answer questions about who a character is or how they are portrayed.
  • I4 (learn): Silver data or generated text could be checked against a reference frequency profile, with features that should be common but are missing, or present but impossible, used as diagnostic negative controls.
  • I5 (answer): Readers for fables and tales should treat dialect marking in dialogue as deliberate characterisation, not as evidence about real language use, and should not let it skew grammatical expectations learned from other genres.

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

 Institutions

🎓University of MannheimMannheim · Germany18 works · 6,984 citations🎓Université de StrasbourgStrasbourg · France8 works · 2,805 citations

📚 Shelves 3 Arts and Humanities · 9,296 works Language and Linguistics · 9,206 works Literature and Literary Theory · 340 works

🧭 Topics 1 English · 1,373 works

Cite

Cite as Michael Percillier and Catherine Paulin. 2017. Postcolonial Literature and World Englishes: A Corpus-Based Approach of Modes of Representation of the Non-Standard in Writing. International Journal of Literary Linguistics 6.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.15462/ijll.v6i1.102

@article{percillier2017postcolonial,
  title = {{Postcolonial Literature and World Englishes: A Corpus-Based Approach of Modes of Representation of the Non-Standard in Writing}},
  author = {Michael Percillier and Catherine Paulin},
  journal = {International Journal of Literary Linguistics 6},
  year = {2017},
  doi = {10.15462/ijll.v6i1.102},
  url = {https://doi.org/10.15462/ijll.v6i1.102}
}

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