Sarcastic Feminism: A Lexico-Syntactic Analysis of Judy Syfers’ I Want A Wife
Bibliographic record
Abstract
This work examines the relationship between language and the plights of women as espoused by Judy Syfers in her text “I Want a Wife”. It seeks to establish the concerns of the writer and the choices she made in her agitation and struggle for women liberation. To achieve this, Feminist CDA approach was adopted in order to critically identify the implications of the writer’s lexical items within the context of her language. This would enable us demystify her language and see how gender power is constructed; see where women are placed on the ladder of power and the effort the writer makes to ameliorate the social status of women. Thus, attention was given to lexis and syntax (noun phrase). This helped us to find out that the context in which the writer agitates for women liberation is within the family and its attendant responsibilities. It was discovered through the examination of syntax of the language that the use of sarcasm and rankshifting were paramount. Through rankshifting, the writer presented the enormity of women’s plights, and condemns such man-made, imposed and killing plights using sarcasm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".