Linguistic Tensions in a Professional Accounting Field: English Linguistic Capital, Hierarchy, Prestige, and Distinction Among Accountants†
Bibliographic record
Abstract
ABSTRACT This study examines the processes by which English linguistic capital is legitimized as integral to professional accountants' distinction, prestige, and status in Jordan. Drawing on 27 interviews, the study reveals the dynamic and mutual interdependency of social hierarchies and Jordanian accountants' agency in embedding the English language in everyday practices and routines. Accountants in senior positions employ English linguistic practices and strategies linked to the global structures of the profession (e.g., IFRS, enterprise resource planning [ERP] systems, Big 4 firms). Typically, these respondents already have a good command of English due to their elite, socially and economically privileged upbringing. By comparison, less powerful accountants, not drawn from the elite, tend to accept and internalize the need for English in their field, despite being more proficient in Arabic. They employ coping strategies that largely reinforce their marginalization, although occasionally they are able to open up spaces for hybrid linguistic practices, as they adapt the use of Arabic and English to their practical, daily requirements. The data also suggest that all Jordanian accountants in this study, regardless of social background, experience emotional ramifications linked to the tensions between the global demand for English in their field and meanings associated with English and Arabic due to colonial history. Through the lens of Bourdieu's sociolinguistic and practice theory(s), Jordanian accountants experience frictions and internal contradictions, “split habitus/habitus clivé,” driving them to compartmentalize (decouple) their Arab and professional identities in a global accountancy context. Insights emanating from the study have implications for understanding and addressing unequal power and marginalization in professional accounting settings in Jordan and beyond.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".