The Sociology of Exclusion: A Knowledge Synthesis of Imperialism, Colonialism, and Postcolonialism in Accounting Research<sup>*</sup>
Bibliographic record
Abstract
ABSTRACT The ways in which accountancy (accounting, accountability, and accountants) has been a device of imperialism, colonialism, and postcolonialism, and therefore has had deleterious effects on Indigenous peoples in former colonies and continues to negatively impact immigrants in postcolonial OECD countries, is under‐researched. This structured literature review synthesizes studies in the accounting literature that have investigated imperialism, colonialism, and postcolonialism and identifies opportunities for future research. This study is part of a broader research project that reviewed 161 articles on accounting and discrimination. This article, based on 65 of the articles reviewed for the broader project, discusses existing knowledge on imperialism, colonialism, and postcolonialism. The author finds that the exclusion of Indigenous peoples in colonial times is shaped by perpetual oppressive relations. In the postcolonial United States and Old Commonwealth countries (Canada, Australia, and New Zealand), these power relations are sustained by professions through the continuing exclusion of racialized people and immigrants, many from previous colonies. This study proposes future research directions to advance the decolonization of accounting research by foregrounding alternative perspectives of Indigeneity—such as Black Indigeneity—and enabling accounting scholars to confront the various subthemes of imperialism and postcolonialism in accounting, including Western accounting and accountability, professionalization, emancipatory accounting, and Indigenous knowledge and accounts.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".