Enhancing community investment in Canada: what can be learned from the U.S.?
Bibliographic record
Abstract
This study looks to the American community investment sector for lessons that could enhance the Canadian community investment sector and improve citizens' access to credit. The report argues that, though a burden of responsibility for the 2008-09 credit crisis can be placed on the American financial services sector's lack of regulation, this does not discount the contribution the United States continues to make regarding innovations in community credit. Canada's heavily regulated financial services sector serves the majority of Canadians well, but may not serve all of Canada's citizens. Canadian thinking on the delivery of financial services can gain insight from the progressive environment resulting from the American Community Reinvestment Act. This study presents Canadian and American community investment strategies, techniques, policy and legislation in a comparative structural framework to better identify American innovations that could be adapted to enhance community investment in Canada. Through a literature review and interviews with five leading experts in community investment, the study draws several conclusions. It agrees with previous researchers who assert that Canada could benefit from a broad national framework for community investment to help unify organizations and help overcome barriers posed by working within Canada's vast geography and sparse population base. It also contends that Canada's traditional policy approach, which siloes economic and social policy and provides economic analysis based on regions or sectors rather than communities, is a barrier to creating the national perspective that the community investment sector requires. The robust and innovative community investment sector in the United States was developed in response to a local context. Canada's own community investment sector can benefit not only from considering American innovations, but also from the adaptation of lessons learned from that exploration to support access to capital within Canada's own unique environment. --P
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".