Bibliographic record
Abstract
Foucault believed an ethical person developed through “self forming activity” and the exercise of free will. Foucault’s theories on ethics and power-knowledge, however, can be viewed as a contradiction. The problem, say his critics, is that self-forming activity should not be possible in an environment dominated by power-knowledge. Foucault did not address this apparent contradiction in the few years he had remaining. He did briefly comment that they were compatible and had always been throughout his work; he had just not been aware of it. The dissertation also discusses the matter of free will necessary for ethical “self forming activity”. Again, Foucault was largely silent on that issue but it is possible to deduce his standpoint. To argue these points, it is necessary to answer the common criticisms that Foucault was caught in a discourse that inhibited objectivity, that his personal ethics coloured his theory, and that he provided nothing new to Western philoso! phy. In an attempt to resolve these issues, the author combines Foucault’s theories on ethics and power-knowledge by pairing them for practical application. The model is applied to the Canadian Forces, which has a well-developed ethics program and obvious power-knowledge network. The synthesis of Foucault’s theories, however, reveals a contradicting ethic of statism and a parallel power-knowledge system of bureaucracy and dysfunctional, executive officer personality type.
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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.041 | 0.077 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".