Altruism of Aid:Analysis of Canadian Official Development Assistance (ODA) into Sub-Saharan Africa (SSA)
Bibliographic record
Abstract
Introduction 2. Background and Literature Review 2.1 Historical Context of Sub-Saharan African Economic History 2.2 Schools of Thought on the Altruism of Aid 2.3 Efforts of Canadian Bilateral ODA into Sub-Saharan Africa 2.4 (In)effectiveness of ODA in Ethiopia 3. Data and Methodology 3.1 Data 3.2 Methodology 4. Findings 4.1 Altruistic v. Weak Altruistic Cases 4.2 Examination of the Official Languages of Altruistic Aid Recipients 4.3 Geographic Exploration of Altruistic Aid Recipients 5. Discussion 5.1 Comparison of Outcomes with Other Models 5.2 Case Study of Canadian-Ethiopian Bilateral Aid 5.3 Case Study of Altruism in Chinese ODA v. World Bank Aid 6.Conclusion 6.1 Limitations and Future Research 6.2 Key Takeaways and Implications 7. Appendix Appendix A: Table of Countercyclical Donations from Canada from 2010 to 2020 Appendix B: Total bilateral ODA from Canada to Ethiopia from 2017 to 2023
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".