Experiences establishing a new speech-language pathology training program in Ethiopia, a resource-limited setting: Lessons learned
Bibliographic record
Abstract
PURPOSE: Ethiopia is the second most populous country in sub-Saharan Africa. While Ethiopia's health care system includes primary health centres, general, and specialised hospitals, allied health care like speech-language pathology was not available until 2003. This article was written with the aim of sharing the experience of establishing speech-language pathology as a profession and the first speech-language pathology training program in Ethiopia. METHOD: In this paper, we retrospectively examine how the leadership of local stakeholders, a multidisciplinary team, and the development of a professional infrastructure led to the success of the program. The authorship group, who were involved in the program from inception to implementation, share their experiences. RESULT: The speech-language pathology undergraduate program at Addis Ababa University graduated its first class in 2019. Plans to grow the training program at the graduate level are ongoing. CONCLUSION: This novel program, grown from several international partnerships, is an example of how low- and middle-income countries can improve access to the service providers necessary to treat their populations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".