Bibliographic record
Abstract
Until now, assessments of the scope of enterprises in Canada that are owned by government have placed Canada roughly in the middle of OECD member countries in terms of how much direct control governments have over businesses in our economy. But that’s because all of those assessments have relied almost strictly on counting federal Crown corporations. For the first time, this study takes into account businesses owned by lower levels of governments. And once they are accounted for, it becomes clear that the size of Canada’s state-owned enterprise (SOE) sector is dramatically bigger than previously thought. In fact, the provincial Crown sector alone is significantly larger than the entire federal sector, whether we measure by assets, employees or contribution to national GDP. Add the assets of provincial Crown corporations to the federal ones and the combined sector turns out to be nearly two and a half times larger than the federal sector alone. Measured by contribution to GDP, the provincial sector and federal sector together account for nearly five times as much as the federal sector on its own. But even this seriously understates the true scope of government-owned enterprise in Canada, since it does not account for what are certainly hundreds more municipally owned corporations. Getting a handle on the actual size of the undoubtedly substantial municipalSOE sector, however, has proven to be difficult, due to the dispersion of records and the differences in how government-affiliated businesses are structured and defined from city to city (and even within the same city). But one thing is certain: Canadian governments own a sizeably larger share of the national economy than past studies have suggested. The share of the economy that is controlled by government is something Canadians need to have a much clearer idea about: In the past, Canadian governments have privatized many of the most visible state-owned businesses, from Air Canada and Petro-Canada at the federal level, to Manitoba Telephone Systems and Nova Scotia Power Corp. at the provincial level. With a better understanding of the size, and structure, of the government-owned enterprise sector, Canadians may wonder if there is still much more room for privatization. It is possible that may not be the case. But until Canadians have clear information about the government’s ownership stake in the economy, informed decisions about the further privatization of Crown corporations are not possible.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".