Barrier Factors in the Integration of Professional Accountants Trained Abroad: Literature Review
Bibliographic record
Abstract
Several theoretical currents have been mobilized in the literature to understand factors of barriers to integration. Numerous studies have been carried out and the results obtained differ from one context to another. In addition, new barriers emerge with each study justifying the need for an exploratory approach to better understand the subject. The objective of this article is to review the literature with the aim of proposing a conceptual framework bringing together the various factors of barriers to integration that have been identified so far in the literature. In our work, we focus on accounting professionals trained abroad when they immigrate. The regulated profession of chartered accountant is a special case of the closed market with access control to the profession, reserved tasks and guarantees of technical competence (Paradeise, 2008). Following the interactionist sociologists of Chicago, numerous works, dealing with a great diversity of professional groups, have shown how these are built and recomposed in ceaseless struggles and negotiations, both at their borders and at their heart. The accounting professions, and in particular the accounting profession, illustrate this phenomenon in different national contexts (Dietrich & Moysan-Louazel, 2012: p. 5). We come to the conclusion that unlike studies on cultural, economic, social capital, and collectivist and individualist factors, the aspect of information has been very little used by the authors. Most studies on barriers to integration have focused on the qualitative methodology in data analysis. As a data collection tool, a large number of studies have used interviews or documentary analysis, and the results found differ from one context to another. This poses a problem of generalization of the results obtained. Most studies have focused on factors beyond the immigrant’s control (race, class, etc.) very few highlight the factors under the immigrant’s control such as (skill, training, etc.). …). In the rest of our work, we take a tour of the various theoretical currents mobilized in the literature.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.018 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".