Language and Gender Representation in Chinua Achebe’s Things Fall Apart
Bibliographic record
Abstract
This article examines the linguistic construction of gender in Chinua Achebe’s Things Fall Apart. It shows how this reflects the social reality of the relationships between women and men in society, which is firstly structured in the unconscious mind. The examination of language use in constructing genders in the novel is important as it unveils the relationships between the male and the female in society. This is because gender representation is influenced by unconscious and hidden desires in man. This study specifically examines Achebe’s use of grammatical categories in the construction of the male and female genders in Things Fall Apart. To this end, it reflects the pre-colonial Igbo society in its socially stratified mode, which language served as the instrument for both exclusion and oppression of women. This article shows that the male and female genders dance unequal dance in a socially, politically and economically stratified society where the generic male gender wields untold influence over women in that pre-colonial Igbo society. The study further shows that Achebe used language in Things Fall Apart to glorify masculine gender while portraying the female gender as docile, foolish, weak and irresponsible second-class citizen.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 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".