Linguistic Turn and Gendering Language in the Cambridge Advanced Learner’s Dictionary
Bibliographic record
Abstract
<p>Language constructs how humans perceive things. Since language is a human construction, it tends to be biased as it is mainly men’s construction. Using gender perspectives, this paper attempts to discuss the imbalance in gender representations found in the examples given in an English learner’s dictionary, that is, the <em>Cambridge Advanced Learner’s Dictionary, 3<sup>rd </sup>Edition</em>. A learner’s dictionary is chosen because it is where one can find and learn the meaning of words. The results show that linguistically speaking, English is still a highly patriarchal and gendering language where men are portrayed better than women. Women tend to be subjugated under men’s domination. Sexism and patriarchy still overshadow the meanings of words characterizing men and women. This means that men are still considered to be dominating women, despite the fact that the feminist movement has been going more than thirty years. Consequently, English language teachers should balance the gender bias by providing addtional materials that are gender neutral.</p>
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".