Building Bridges Between Policy and Praxis: A Comparative Environmental and Policy Scan of Inclusive Education in Ethiopia and Canada
Bibliographic record
Abstract
This article provides a pioneering glimpse into the environmental and policy realities of inclusive education in Ethiopia’s and Canada’s educational systems. As co-signatories to multiple international commitments toward inclusive education development and implementation, including the Salamanca Statement (United Nations Educational, Scientific and Cultural Organization & Spain Ministry of Education and Science, 1994), Canada and Ethiopia have demonstrated strong policy pathways that support these international goals; however, several obstacles have hindered compliance and results. These obstacles include, but are not limited to, gender bias, lack of resources, climate challenges and disasters, COVID-19, political volatility, and policy breakdown. These obstacles ignited our central motivation to complete a comparative policy and environmental scan of inclusive education in Ethiopia with Canada’s inclusive education landscape as a backdrop. By gathering and examining political and environmental facts from over the past century for each country, including decades of policy documents and correlating statistical information, we, who have been actively engaged in Ethiopian educational development for over a decade with an international non-governmental organization, propose a new responsive theoretical framework as a guidance system for integrated-inclusive education using collectivism and individualism to bridge the gap between policy and praxis.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".