WHO-FIC Education Committee: A Status Report 2006-2007
Bibliographic record
Abstract
The WHO-FIC Education Committee was established at the 2003 WHO-FIC Network meeting in Cologne, Germany, as a successor to the Subgroup on Training and Credentialing of the WHO-FIC Implementation Committee. New terms of reference were developed at the Cologne meeting to reflect generic tasks for education and training on the International Statistical Classification of Diseases and Related Health Problems (ICD) and the International Classification of Functioning, Disability and Health (ICF). Specific tasks have been agreed for both ICD and ICF. The principal ICD tasks relate to an international training and certification program for ICD-10 mortality and morbidity coders; this program is being developed in conjunction with the International Federation of Health Records Organizations (IFHRO), a non-governmental organization in official relations with WHO. A Joint WHO-FIC – IFHRO Collaboration (JC) was established in late 2004 to carry forward this work (see separate paper). The JC held its third meeting in Washington, D.C. in May 2007, in cooperation with the WHO-FIC Education Committee (EC). The purposes of the meeting were to advance work on the International Training and Certification Program; receive reports on the project to pilot the program for underlying cause of death coders and trainers in Canada and Korea; prepare for the 15th IFHRO Congress in Seoul, Korea; address other Education Committee tasks and make plans for the 2007 WHO-FIC Network meeting. During the IFHRO Congress, the JC awarded its first certificates to underlying cause-of-death coders and trainers and recognized underlying cause-of-death training materials from three countries as meeting the JC standards. The JC and EC continue to solicit and review ICD-10 training materials and have developed a core curriculum for training certifiers of cause of death, which is posted on the EC website along with previously developed core curricula for ICD-10 mortality and morbidity coding
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 | 0.022 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.028 |
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".