Modeling global transfusion medicine education
Bibliographic record
Abstract
This document provides an analysis and oversight of the necessary educational infrastructure at national level needed for successful and sustainable education programs undergraduate and post-graduate and is focused on desired outcomes needed to secure general Transfusion Medicine (TM) competence and basic skills when appointed in a professional TM position. It provides a global model framework for TM education allowing individual countries to tailor the context and contents of the institutional curriculum. Education in transfusion medicine is a complex set of intimately interrelated and interconnected components that allow student and fellow exposure to knowledge and skills, the ultimate curriculum. The extent to which knowledge and skills, professionalism and leadership principles are offered depends on the expected outcomes needed for the desired roles, tasks and functions. A model for the development and implementation of an education (teaching and training) curriculum in Transfusion Medicine aimed at medical students and doctors, nurses and midwives, and laboratory professionals should ideally include an outcomes-based component, with clear recommendations on the required roles, skills, attitudes, and knowledge of a trainee completing such a curriculum. This should correspond to the environment and scope of practice required from such a vocational or academic professional and should address deficiencies in knowledge, skills and attitudes present before the curriculum is completed, while taking into account fundamental international standards of knowledge and the needs of their working climate and environment. Therefore, it is considered more practical to provide a set of outcomes that would be useful in most contexts and settings, while equipping students, as adult learners, with the tools for advancing their educational, professional and leadership development suited to their availability and socio-economic environment. The framework or model recognizes that no one set of education or training initiatives will be appropriate in all countries or settings and should be tailored to specific settings based on the assessment of local needs and available environments.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.004 |
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".