EXPANDING THE BODY OF KNOWLEDGE CONCEPT FOR PROFESSIONAL PRACTITIONERS
Bibliographic record
Abstract
In recent years, the emergence of many newdisciplines and the increasing depth of existing disciplineshave prompted the development of the Body of Knowledge(BoK) concept in order to improve the uniformity of newundergraduate programs in accredited professionalschools, and to provide a requisite standard forcertifications in vocational education. A body of knowledgeis the collected wisdom, experience, processes, and factsthat both inform a profession and provide the solidfoundation from which continuous improvements andinnovative change can occur. This paper provides arguablythe first summary of 32 BoK examples, and proposes a newmodel of a BoK for professional practitioners
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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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.007 | 0.050 |
| Scholarly communication | 0.017 | 0.035 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".