Allowing Charities to “Do More Good” through Carrying on Unrelated Businesses
Bibliographic record
Abstract
One way in which charities could increase their positive impact on society is by raising revenue through carrying on a business. Current income-tax legislation in Canada, however, restricts the ability of charities to do so by prohibiting them from carrying on an unrelated business. This article reviews the current law and explores the options for loosening this restriction, while at the same time addressing the potential problems associated with charity-operated businesses. In the end, the author recommends that all charities except private foundations be permitted to operate small businesses, so long as the business activities are disclosed to donors. Les œuvres caritatives pourraient augmenter leur impact positif sur la société en faisant accroître leur revenu au moyen d’une activité commerciale. Au Canada, cependant, la loi actuelle de l’impôt sur le revenu restreint la liberté des œuvres caritatives en les interdisant de gérer un commerce sans lien avec leur activité principale. Cet article passe en revue la loi actuelle et explore les options pour libéraliser la loi, tout en recensant les problèmes potentiels associés aux commerces qui seraient gérés par des œuvres caritatives. Au bout du compte, l’auteur recommande que toute œuvre caritative à l’exception de la fondation privée ait la permission de tenir une petite entreprise, en autant que l’œuvre mette ses donateurs au courant de son activité commerciale.
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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".