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KEEPING ABREAST OF TIME FOR FUTURE CHALLENGES

2013· article· en· W4248703961 on OpenAlexaboutno aff

Bibliographic record

VenueCONTEMPORARY MILITARY CHALLENGES · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)Computer scienceTerm (time)Operations researchRisk analysis (engineering)Operations managementPolitical scienceBusinessProcess managementEngineering

Abstract

fetched live from OpenAlex

This year, the transformation of the Slovenian Armed Forces continues. Last year, the guidance on reduction of defence budget continued from the previous years. This required a thorough reflection, preparation of measures and constant upgrades in the defence system functioning. In the overall effort to apply cuts to defence budgets, NATO member states searched for various solutions and each of them tackled this challenge in a slightly different way. The term transformation is thus a very topical term. We have heard and read a lot about it. However, in the last year, Smart Defence was certainly the one most related to the reduction in defence budgets. And what is the essence of Smart Defence? It is no longer about how to achieve more with less, but how to use the given resources to maximise the efficiency. This also requires changes in thinking, approaches, and mainly solutions. NATO member states considered different options to achieve best results in the current situation. The synergy of effects is supposed to be the right option for everything, whereby all of the engaged entities should contribute to the best of their abilities and in a way to best build an effective whole. In the Slovenian Armed Forces, we have considered the given circumstances, studied our possibilities and with a new year we started a journey down the path of optimal functioning and changes. This process was called transformation of the Slovenian Armed Forces. It is just that topical issues from the domestic and inter- national security environment are also discussed in our contributions. Some of the authors thus present their works and findings developed recently during the transfor- mation process. In this issue, Vinko Vegič is publishing his article »NATO crisis interventions – lessons learned and challenges of the operation in Libya”. He describes what such a vast NATO operation means and what it brings in practice, i.e. in a situation where different doctrines and theoretic debates should provide appropriate solutions. Branimir Furlan wrote the article »Professional armed forces without professional autonomy – is this possible?” where he shares a view on the developmental phases of the professionalization of the armed forces and military profession as the final goal bringing to foreground the question of competence and responsibility of the military for its own professional development. Valter Bosotina and Branko Lavtar discuss “The renovation of uniform-supply system in the Slovenian Armed Forces”. In their article, they present the solutions for the improvement of the process used so far, which is necessary for the functioning of the Slovenian Armed Forces. The process is, at the same time, affected by various circumstances and influences, which require changes. In his article “New approach to prediction and decision-making in the targeting process” Jurij Jurtela presents a subject which deals with fire support systems. He acquaints readers with the dilemmas that occur during individual military operations and require decisions about a great variety of matters. He provides suggestions on how to tackle those dilemmas and what tools to use for the best effect and superiority. Erik Kopač and Janja Vuga from the Faculty of Social Sciences write about Individual’s choice to seek employment in the Slovenian Armed Forces contract reserve. They used socio-psychological approach to study, which factors are the most decisive for this type of employment, and established that economic stimula- tion plays an important role in this, while the essence lies in the personal attitude of each individual. More details are available in the article. Canadian anthropologist Donna Winslow studied modern defence forces. She authored a number of articles and reached many interesting findings. Two of the most famous include the findings about a scandal in Somalia and about the war in Chechnya. Maja Garb, Jelena Juvan and Uroš Svete honoured her memory with their article “From the questions of military culture to the analysis of anthropologi- sts’ role in the armed forces – the work of Donna Winslow”.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.065
GPT teacher head0.276
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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