A Comparative Investigation of Gender Terminology in the Egyptian and Tunisian Constitutions
Bibliographic record
Abstract
Abstract Gendered language is becoming a matter of serious concern for legal drafters and policymakers because 'it is always changing as societal views change' (The University of Calgary: Office of diversity, equity and protected disclosure 2017:1). Many western countries have made considerable progress towards using inclusive legal language. However, inclusive language is not implemented in other parts of the World; the Arab World is no exception. This may be due to the violation of language rules, the decline of language, and the lack of enough evidence that changing the language will change society (Brown in ABA J, 2019) and (Brown in ABA J: 24–26, 2018). In this paper, I explore the challenging socio-cultural and linguistic factors that may hinder the implementation of gender-inclusive language in Arabic and explain the current situation in two current constitutions of Egypt and Tunisia in particular. The main aim of this paper is to conduct a comparative analysis of terminology representing gender in the Egyptian (2014, amended 2019) and Tunisian (2014) Arabic-English Constitutions using corpus-based tools. The analysis shows inconsistent attempts at a more inclusive source text through using neutral terms and adding inclusive pre-modifiers to these terms. It also shows inconsistent translation of gender-specific terminology and pronominal references. Both constitutions explicitly stress the ‘eradication of violence against women’ and express parity between ‘women’ and ‘men’ in terms of ‘equal rights’ and ‘appropriate political representation’ (e.g. in the Egyptian House of Representatives (28%) and the Tunisian Assembly of People’s Representatives (26%)) (International Institute of Democracy and Electoral Assistance, IDEA 2021). Although these percentages are not far away from the representation of women in European countries such as the United Kingdom (35%) (International Institute of Democracy and Electoral Assistance, IDEA 2021), it is the reality of women’s actual roles, change they initiate and their impact in the society that counts.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".