Ett nödvändigt ont? Truppminors taktiska påverkan i ljuset av modern krigföring
Bibliographic record
Abstract
This study examines the effects of the presence of anti-personnel mines on the use of tactics during the battle of Hürtgen forest 1944. The study aims to contribute to the ongoing debate regarding withdrawal from the Ottawa Treaty and argues that there are discrepancies in previous research regarding the effect of anti-personnel mines. By analysing the effects of anti-personnel mines through the lens of Stephen Biddle’s (2010) Modern System-theory the study aims to research the possible tactical effects of the weapon. A ‘Structured, Focused’ method is applied in order to analyze the empirical material. The results suggest that the presence of anti-personnel mines affected the use of tactics to some degree, primarily through restricting movement. Furthermore the study finds no pattern between the class of minefield and its effects. The effects of anti-personnel mines in the Hürtgen forest instead seemed to vary based on the tactical situation and terrain. For further research an explanation building and a theory developing study is proposed in order to further develop the understanding for anti-personnel mines as a whole.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.008 |
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".