The Practice of Tax in Canada: Understanding the Community, the Work and Structural Initiatives of an Emergent Profession
Bibliographic record
Abstract
Considering it as a distinct occupation, I investigate the practice of tax in Canada through three separate studies. My first study examines the community of tax practitioners. Using a mixed-method approach, I integrate the insights obtained from in-depth interviews with 38 professionals and the results of a survey of 116 individuals working in the tax area. The notion of collective identity is used to confirm the existence of a distinct occupational community and to elaborate the suggested boundaries. I introduce the concepts of boundary erasure and boundary emergence into the literature as variants of boundary blurring and boundary making to suggest how the boundaries of a field can be reconfigured. Analyzing the work of tax practitioners, my second study maps the sets of tasks that characterize the tax field. Drawing on Abbott’s (1988) theorization on professional work, I explore the nature of the specific expertise involved in tax and explain how it differs from the expertise associated with the work that accountants and lawyers more traditionally perform. The framework I develop offers a more integrated understanding of tax work, which can be used to explain why neither the accounting nor the legal profession have come to dominate the core of the field. My third study considers the aspect of structure in the Canadian tax field. Relying on a review of archival material, as well as in-depth interviews with 29 closely associated individuals, I examine the most far-reaching effort to accredit tax specialists in Canada, an initiative by the CICA, which occurred between 1997 and 2002. Finding that the professional associations, the national firms, and the rest of the membership were each driven by different interests, ranging from narrower individual concerns to broader professional ideals, I suggest that the conflicts between the different segments contributed to the ultimate demise of the initiative. Developing a more integrated understanding of the field, my studies have implications for future research on tax professionals. They should also assist those charged with training practitioners, and be of interest to the profession more widely, particularly those wishing to recognize or govern tax work more formally.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.039 | 0.019 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".