CROSS-ANALYSIS OF DATA COLLECTED ON KNOWLEDGE MANAGEMENT PRACTICES IN CANADIAN FORCES ENVIRONMENTS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As the 21st century unfolds, a number of changes have already altered the character and conduct of military operations. Consequently, the military profession is subject to drastic transformations, which ones oriented our attention around questions such as how is professional military expertise currently built, shared and transmitted in this ever-changing and unstable world? Drawn on data collected from a recent research on Knowledge Management (KM) practices, namely on Knowledge Creation, Learning and Collaboration, the present work performs a detailed comparison of the states of these practices between the different military environments, with an emphasis on what distinguishes the Army from the others. This paper underlines the components that can be considered either as levers or constraints for the current Canadian Forces KM efforts, such as becoming a knowledge-based army, reaching acute situational awareness or accessing knowledge in the C4ISR context.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it