Europe without Soldiers? Recruitment and Retention across the Armed Forces of Europe
Bibliographic record
Abstract
Europe Without Soldiers? Recruitment and Retention across the Armed Forces of Europe edited by Tibor Szvircsev Tresch and Christian Leuprecht Kingston, Ontario: McGill-Queen's University Press, 2010 272 pages $85.00 [ILLUSTRATION OMITTED] This book is a collection of papers presented at the Tenth Biennial Conference of the European Research Group on Military and Society (ERGOMAS) at the Swedish National Defense College in Stockholm in June 2009. In total, the fifteen chapters and introduction cover a wide variety of issues in a host of European countries focused on the subjects of recruitment and retention. Chapter authors represent a diverse field of academics, researchers, military sociologists, historians, and political scientists. The collection of narrowly focused chapters are loosely organized into four topics: demographic aspects and minorities in the armed forces; conscript-based armed forces and recruitment; the professionalization of armed forces; and the recruitment and retention of professional soldiers in the armed forces. Fortunately, the editors have prepared an overarching introduction that distills the independent findings into broad conclusions while highlighting the notable offerings contained in each chapter. Having abandoned conscription as a national policy nearly forty years ago, an American might ask what could possibly be gained by wading through a book solely focused on Europe's growing pains with the same transition. Those calling for a return to conscription as a means to reconnect the United States' people to the United States' armed forces will be equally disappointed to learn that two of the three countries featured in the conscription section have subsequently abandoned the practice, most notably Germany. For all the differences between the United States and Europe, common themes do emerge such as the influence of demography, education, personal values, health, and the effect of expeditionary operations. As it turns out, the United States is not as unique as we often think it is, at least when it comes to gathering the raw material to build an army and retaining those who have been trained. Tradeoffs associated with quality versus quantity are present on the Continent and in the United Kingdom. The volatility of the labor market precludes long-term planning as well. And perhaps the most interesting term to emerge from the book, post materialist, captures the idea that European youth is just not that interested in national service. …
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".