EVALUATION OF THE DETERMINANTS OF CLINICAL MEDICINE TRAINING OUTCOMES IN WESTERN KENYA
Bibliographic record
Abstract
Study Objective: To analyze the learner – lecturer / instructor interaction process within the context of theory learned during training put into clinical / medical practice. This was in order to generate limitation in both the teaching institutions that address Clinical Medicine training outcomes. Study Design: Across- sectional study Study Setting: This study was carried out in Lake Basin Region of Kenya. The area includes Kisumu and its surrounding counties of Vihiga and Nandi. Study Subjects / Participants: Sixty six (66) Clinical Medicine students from various MTIs in Lake Basin Region of Kenya, 58 health workers, 3 heads of departments from KMTCs, and 5 heads of departments in the clinical placement sites that was visited for this study and 4 lecturers of MTIs. Study Results: Analysis from observations of student / lecturer / infrastructure / leadership / linkage engagements were obvious and more so the absence of libraries in all RHTCs. In both the county Hospital and the referral Hospital (JOOTRH) there were libraries which were inaccessible to Clinical Medicine students. There were linkages and networking processes in all the training health facilities that were used as clinical placement sites. This was evident in the many students who were present from different MTIs in Kenya. Students for clinical placements came from all MTIs in Kenya among who were all KMTCs, GLUK, Uzima University College, Mt Kenya University, Moi University and others. There were evident interactions in many ways both academically and socially, and with the presence of ICT services, these students were linked together nationally regionally and internationally Study Conclusion: This study therefore provides a tool to guide MTIs and clinical placement sites in Kenya on the best practice in linking theory based learning with clinical practice in achieving quality, competent, effective, and efficient Clinical Medicine training outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".