Towards a Rural Development Policy: Lessons from the United States and Canada
Bibliographic record
Abstract
Despite the large sums of money spent to ostensibly support rural areas since the 1930s, a framework for assessing U.S. and Canadian rural policy is conspicuously absent, and thus there is little basis for assessing effectiveness of public policy and public expenditures in this area. The purpose of this paper is to propose a framework based on: 1) broad-based policy ob-jectives; 2) a small number of measurable targets that reflect these objectives; and 3) evaluation based on the latest methodological and data advances. We provide an overview of policies and programs in the U.S. and Canada that have been described as rural policy. Using basic descriptive evidence we show that to date the purported rural policy in both countries has generally failed to meet any broad-based objectives. We suggest that successful rural policy is primarily place-based, rather than being captured by tangential objectives such as support for particular sectors or initiatives such as environmental protection. We conclude by noting that government ministries that administer place-based (rural) policy should not have a sector-based orientation—rural policy should be removed from USDA and Agriculture and Agri-food Canada.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| 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".