Building the de-risking state: Power, policy and Canada’s Social Finance Fund
Bibliographic record
Abstract
In 2018 the Canadian Government announced the Social Finance Fund, a $755 million pool of public capital with the purpose of accelerating the growth of social finance markets in Canada. The Fund promises to unlock large new sources of funding for social purpose organizations by de-risking private investments (reducing investor losses by providing capital that will be lost first in case of investee default), dually offering investors financial returns as well as an opportunity to do social good with their capital. While the literature has interrogated the theoretical contradictions present in social finance markets, there has been little attention to how social finance markets emerge through acts of policy, and how de-risking private capital becomes a priority of the state. This paper examines how the changing network of actors over decades of policy debate led to the evolution and launch of the Social Finance Fund. The paper also argues that international policy learning was critical to the prioritization of de-risking private investments in social finance markets.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".