Male Chauvinism in Cameroon Pidgin English: The Case of the Collocates of Man
Bibliographic record
Abstract
The aim of this paper is to assess the creative and dynamic uses of the collocates of man in Cameroon Pidgin English as it has picked up chauvinistic connotations in a strict and increasingly patriarchal Cameroon. Cameroon Pidgin English has been analyzed from different perspectives by different scholars, but the area of collocation has seldom been tackled. Word associations like ‘speak like a man’, ‘drive like a man’, ‘man-boy’, ‘my man’ (penis),’ he is a real man’ ‘man hand’ etc. abound in the repertoire of Cameroonian users of English. This paper thus brings out the different possible collocations with the word man as well as semantic degradations and ameliorations in the Cameroonian context and investigates if the continuous dominance of (the) man in the Cameroonian society could be a subtle case of linguistic rights violation. This study uses participant observation, interviews and questionnaires to obtain data from 100 speakers of Cameroon Pidgin English in Cameroon.This study employs the social identity theory propounded by Henri Tajfel and John Turner (1979; 1986) which explains intergroup behaviours and status differences. Results show that the domains of use cut across the domains of the traditional ruling system, titles and kinship terms, professions, traditional economic system and foodstuffs and drinks. Also, man is used in Cameroon Pidgin English for self -expression and self- identification. Most of the collocates of man reflect the sociolinguistic background of the country with most of the terms having come from background languages like French, Cameroon Pidgin English and Camfranglais.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".