Bibliographic record
Abstract
Non-profit corporations benefit from significant tax subsidies, but they are largely regulated by corporate statutes rather than tax law. Recent legislative reforms in Canada have sought to modernize non-profit statutes to reflect the changing non-profit sector, with a focus on increasing accountability and fairness. Yet, despite the increasingly national reach of non-profits, governance and financial transparency requirements can differ considerably between jurisdictions. This article compares non-profit rules about directors and financial review in Alberta, British Columbia, Ontario, and federally. It demonstrates how modern non-profit law reforms make regulatory choices about governance and financial transparency requirements based on local policy priorities. The article then uses tax expenditure analysis to argue for a national perspective that considers the different regulatory burdens facing non-profits receiving the same federal tax subsidies. It finds that inconsistent rules between jurisdictions raise significant accountability and fairness concerns. For smaller non-profits, uninformed incorporation choices may result in a higher compliance burden. For non-profits seeking a lighter regulatory load, the uneven regulatory landscape may lead to jurisdiction shopping. The article argues that the increased harmonization of non-profit law across Canada is key to continuing the work of modernizing non-profit law. It concludes by identifying potential law reforms and their limitations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".