OFFICIAL DEVELOPMENT ASSISTANCE (ODA) KANADA DALAM UPAYA MENGURANGI KEMISKINAN DAN MEMPERKUAT HAK ASASI MANUSIA DI NEGARA BERKEMBANG DAN AFRIKA TAHUN 2018-2022
Bibliographic record
Abstract
This article aims to analyze the provision of Official Development Assistance (ODA) from the Canadian government to developing countries and African countries to reduce poverty and strengthen human rights in 2018-2022. Canada is a developed country that provides a lot of humanitarian assistance to developing countries and African countries. This raises the question, “What is the role of Canadian ODA in reducing poverty and strengthening human rights in Africa in 2018-2022?” To help answer the question, the authors use the concept of Humanitarian Financing. ODA provided by Canada in Africa is in the form of financial assistance. In conducting research, this article uses a qualitative research method, namely a literature study by collecting various books, journals, articles, and other sources to be able to answer this problem.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".