Canada’s Aid Policy and Assistance to Rural Development and Land Policies to the Philippines since the 1980s
Bibliographic record
Abstract
Concerns over food security and agriculture are back on the agenda for many donor agencies. Canada followed the trend by declaring that food security is one of its three priority areas (CIDA 2009). While these are encouraging and welcome initiatives, one cannot avoid wondering how much Canada has learned from its past experiences, and also how much such focus is rooted in an understanding of the structural impediments and obstacles to rural development. This paper takes a long-term perspective on Canada’s official development assistance (ODA) commitment to land and rural development policies, examining the specific case of the Philippines. In doing so, the paper suggests that Canada’s commitment to land policies and agrarian reform appears driven by specific political conjunctures and moments, rather than a long-term commitment on how to address issues of rural poverty and unequal access to land and resources. So far, on land policies and rural development, the Canadian International Development Agency (CIDA) has talked the pro-poor talk but has failed to walk the redistribution walk.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".