Bibliographic record
Abstract
Organizational conception and business practice share much in common with military strategy. The two areas of study have had a mutually supportive relationship for decades. Particularly since the commencement of the 20th century, the business community has borrowed freely from and refined military thinking. This practice has been in large part credited with the enormous success of the industrial expansion of the United States and Canada. Many of today's multicorporations gained global prominence from adopting and employing military concepts and people. But the phenomenon has not been altogether one-sided. Since the 1970s, the military profession has, in turn embraced organizational thinking and business practices. This paper will focus on the military's attempt to assimilate aspects of management and organizational theory, as well as business experience, to bring direction and meaning to its present and future placement in the 21st century. More specifically, the author will examine the formal strategies of both the U.S. and Canadian Armies within the context of present organizational thinking as taught by leading institutions and utilized by Corporate North America. The author will argue that the penchant of both armies to internalize business concepts and strategies has left the two nations' armies in a perilous situation pertaining to strategy formulation and direction. Using current management and organizational models, the author intends to identify the fundamental weaknesses within the two armies' strategies. More importantly, as both armies engage enterprise-wide transformation, the author will demonstrate how this fundamental weakness in cognition and application has the very real possibility of jeopardizing the relevancy of both nations' land forces.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.024 | 0.049 |
| Scholarly communication | 0.028 | 0.016 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".