Accentuating Identities: Phonetic Variation and Stereotypes in Mediated Glaswegian Performances

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Here you’ll find an online resource to accompany my BAAP 2024 poster. I provide examples of mediated GV performances, and further detail on my methods.

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Mediated GV Character Examples

Below are examples of characters in the dataset with specific coded attributes included.

Example: Liam from ‘Sweet Sixteen’ (2002)

Coded Attributes
Profanity: 5
Weapon Carry: 5
Criminality: Yes
Intelligence: 3
Aggression: 4

Example: Malcolm from ‘In the Loop’ (2014)
GV character contrast with other accented characters

Coded Attributes
Profanity: 5
Aggression: 5
Intelligence: 4
Friendly: 2

Example: Cemolina from ‘The Legend of Barney Thomson’ (2015)
Imitated GV accent

Coded Attributes
Profanity: 5
Aggression: 5
Substance Use: 5
Weapon Carry: Yes

Methods

Accent Classification

  • Due to issue of accent credibility in mediated performances, accents were classified via phonetic and contextual resources to determine a character’s predominant style [2,3].
  • Contextual cues used were:
    • film-internal (e.g., explicit reference to speech variety/origins, and other semiotic resources clothing/lifestyle), - film-external (e.g., production team and actor(s) making explicit reference to the speech variety used, and media/character synopsis).
  • Presence of salient accent markers attempted by actors reinforced accent categorisation (e.g., GV fronted GOOSE vowel, backed TRAP/BATH) [5].

Intercoder Reliability (ICR)

  • To ensure robust agreement between two coders, both overall ICR testing and attribute-specific testing were conducted:
  • The overall dataset achieved above acceptable levels of intercoder reliability (i.e., ≥.70), based on Krippendorf’s alpha:κ = 86%, and greater than would be expected by chance Z=7.51, p<.05.
  • All coded attributes individually achieved acceptable levels of intercoder reliability: i.e., criminality (.93), expletive use (.89) aggression (.81), friendliness (.80), authority (.83), intelligence (.78), trustworthiness (.78).

Statistical Analyses

Non-parametric testing

  • To explore the relationship between accent type and the ordinal-rated coded attributes, non-parametric tests were conducted.
  • Kruskal-Wallis tests found significant differences on attributes according to accent group (Chi square = 15.507, df = 8, p <0.05).
Attribute Kruskal-Wallis Test
Intelligence χ² = 70.778, p < 0.001
Authority χ² = 24.013, p = 0.00228
Friendly χ² = 9.0425, p = 0.3387
Trustworthiness χ² = 8.4566, p = 0.3902
Competence χ² = 83.936, p < 0.001
Warmth χ² = 16.706, p = 0.03332
Profanity χ² = 33.794, p < 0.0001
Substance Use χ² = 17.277, p = 0.02735
Aggression χ² = 22.449, p = 0.004148

Table 1: Attribute-specific Kruskal-Wallis Testing

  • To determine which accent groups may exhibit greater stochastic dominance on portrayed attributes, post-hoc Dunn tests (with Bonferroni adjustments) were conducted.
Attribute Significant Differences
Intelligence GV ≠ RP, SSE, GSE
Authority GV ≠ RP
Competence GV, GenAm ≠ RP, SSE
Warmth EdV ≠ RP
Profanity GV ≠ RP, SSE

Table 2: Significant Differences among accent groups on attributes (Post-Hoc Dunn Test with Bonferroni adjustments) Note that ≠ demonstrates a significant difference from one accent group to another group(s).

Fitted Models

  • CLM and POLR models were fitted, whilst testing interactions of predictor variables (accent, gender, life cycle, role) on attribute ratings.
  • Interaction-based models did not show a superior fit compared to non-interaction-based models:
    (Attribute ~Accent + Gender + Life_Cycle + Role).

References

[1] R. Lippi-Green, English with an accent: Language, ideology, and discrimination in the United States, 2nd ed. Routledge, 2012.
[2] M. Dragojevic, D. E. Mastro, H. Giles, and A. Sink, ‘Silencing nonstandard speakers: A content analysis of accent portrayals on American primetime television’, Language in Society, vol. 45, no. 1, pp. 59–85, 2016.
[3] J. Cohen, ‘A coefficient of agreement for nominal scales’, Educational and Psychological Measurement, vol. 20, pp. 37–46, 1960.
[4] S. T. Fiske, A. J. C. Cuddy, P. Glick, and J. Xu, ‘A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition’, Journal of Personality and Social Psychology, vol. 82, pp. 878–902, 2002.
[5] A. E. MacFarlane and J. Stuart-Smith, ‘“One of them sounds sort of Glasgow Uni-ish”. Social judgements and fine phonetic variation in Glasgow’, Lingua, vol. 122, no. 7, pp. 764–778, 2012, doi: 10.1016/j.lingua.2012.01.007.