Insider Anthropology and the Study of the Canadian Forces Reserves
Bibliographic record
Abstract
The purpose of this paper is to discuss the use of ‘autoethnography’ as an innovative contributor to the field of military and defence studies. Autoethnography is an ethnographic approach that positions the author as the primary subject and utilizes the authors’ self-accounts and reflexive reports, interpreted by the author within a broader social context, to gain a better cultural understanding of a given society. The author is typically an affiliate of the group and, therefore, this method has been commonly associated with ‘insider anthropology.’ Research of such a reflexive and personal nature may allow for insights into problems that traditional ‘scientific’ research may previously have overlooked or unreported. Social science research on the Canadian Forces Primary Reserves is in its infancy and an autoethnographical approach to military and defence studies has the potential to provide insights to such human relations and enhance the understanding of the Canadian Forces as a whole. However, this innovative approach is not without its limitations. In this paper we will further discuss the limits of autoethnography and the potential value of auto-ethnographic reporting to military and defence studies.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".