Does Gendered Language Exist in a Foreign Language Context? A Study in Written Discourse of Saudi Male and Female EFL Learners
Bibliographic record
Abstract
This investigation aims to verify the hypothesis that gendered language exists in foreign language usage as manifested in the EFL learners’ writing output in a Saudi university. The motivation behind this is to, ultimately, check and weed out elements of gendered language that are early on embedded amongst the genders which, with the passage of time, lead to various biases. Though it may be utopian to think of eradicating linguistic bias, yet this study hopes to contribute meaningfully to curb it and substitute the temptation of allowing it to seep into communication, by educating and training EFL users to substitute these with gender-free language and helping ensure greater gender equality. The writing output of 42 EFL learners was analyzed using an electronic parsing tool called Stanford Parser (v. 3.7.0), and all components classified as grammatical dependencies. Results showed that differences existed in male and female writings in the use of noun in subject position which occurred more frequently in female text at 69.15 mean dependency occurrence. This has long been held as a marked feature of female language use. The same dependency stands at a much lower 51.28 mean occurrence in males. Further, female writing has long been associated with a great deal of use of ‘empty’ modifiers, such as ‘very’ which act as modifiers to adverbs and adjectives. The current study upheld this contention as well. Lastly, backchanneling occurred more in female output in EFL than their male counterparts.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".