Evolving Address Terms in Jordanian Arabic: Implications for English Language Learning and Cross-Cultural Communication
Bibliographic record
Abstract
This study investigates the evolving nominal terms of address in the urban community of Irbid City, Jordan, within a broader sociolinguistic framework. Based on 500 instances of naturally occurring address terms collected over six months through non-paticipant observation in public settings like cafés, markets, and service encounters, the study examines how address practices vary across generations, genders, and social-classes. Using qualitative content analysis within a sociolinguistic variationist framework, the findings reveal a decline in traditional kinship-based terms and the emergence of innovative address forms, particularly among younger speakers. These changes reflect broader social transformations and evolving identity dynamics. A comparative analysis with English-speaking contexts highlights linguistic evolution similarities, particularly the informality trend. However, while English address systems increasingly favor first-name usage and gender-neutral terms, Jordanian Arabic exhibits a restructuring process that blends traditional and modern influences. Additionally, the study highlights the implications of address term variation for English language studies, particularly in second language acquisition and cross-cultural communication. Misalignment in address norms between Jordanian and English speakers can lead to pragmatic challenges, emphasizing the need for intercultural awareness in language learning. These findings contribute to broader sociolinguistic discussions, particularly regarding linguistic change, social identity, and globalization’s impact on verbal interaction. The study underscores how address terms function as markers of both cultural continuity and adaptation, offering context-specific insights that may contribute to broader understandings of global linguistic trends in address practices. Future research could explore similar transformations in other non-Western languages, further enriching the discourse on language contact and sociolinguistic variation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".