Tales from the Canadian Tax Code: The Policy and Politics of Federal Tax Expenditure Instrument Choice
Bibliographic record
Abstract
Drawing from 30 in-depth interviews of elite policy actors, this project seeks to add to extant rich descriptions of Canadian federal tax expenditures through a policy instrument choice analysis of the durability of political executives’ interest in tax expenditures. The project proposes a new concept of the politics of Canadian federal tax expenditures. More specifically, the data collected suggests that the use of tax expenditures is motivated by the logic of institutional leapfrogging, which expresses itself in the form of: i) bureaucratic bargaining; ii) public opinion responsiveness; iii) evasive federalism; and iv) government responsiveness to citizenry policy fatigue. The concept of institutional leapfrogging denotes efforts by federal political executives (i.e. Members of Cabinet and their senior advisors) as well as civil service elites to use tax expenditures to deliver visible and popular policy outcomes to the public with minimal interference from other political or governmental actors and institutions (i.e. Members of Parliament, departments of government, and political executives in the provincial-territorial order of government). While I believe that existing understandings of tax expenditures as a politically rational instrument choice are correct, this study departs from earlier conceptual models by examining how such political self-interest is uniquely conditioned by broader Canadian political phenomena. To structure these arguments, I provide background on existing sub-fields of Canadian tax expenditure research and make the case for turning the orientation of federal tax expenditure research upstream in the policy process, toward policy instrument choice theory. I provide an overview of the project’s dependent variable, including a survey of select statistical analyses of Canadian federal tax expenditures. I outline the four independent variables that I hypothesize influence Canadian federal tax expenditure adoption. I then proceed to outlining my research approach, including the methods adopted for elite interviews, as well as the methods used for Hansard and media analysis. Next, I review my research findings, exploring how the project’s data speaks to the causal and intersecting relationship between my independent variables and the durability of tax expenditures. Finally, I offer conclusions on the project’s significance to Canadian political scientists and outline several areas of future research.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.032 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".