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Record W3201078921 · doi:10.17721/2519-481x/2020/69-12

OFFICERS’TRAINING IN THE ARMED FORCES OF CANADA

2020· article· en· W3201078921 on OpenAlexaboutno aff
J. Chernykh, Olena Chernykh

Bibliographic record

VenueCollection of scientific works of the Military Institute of Kyiv National Taras Shevchenko University · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary, Security, and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerMilitary scienceTraining systemTraining (meteorology)Military personnelPolitical scienceStrategic goalPublic relationsOperations researchManagement scienceManagementEngineeringLawGeography

Abstract

fetched live from OpenAlex

Analysis of the foreign experience of the organisation and reformation of the armed forces in other countries, with the respective systems of military education being an integral part, reveals the specific national aspect of such activities in each country. In the meantime, there are some general methodological approaches used in military pedagogic practice across different countries of the world to be practicably considered and applied. The article examines the experience of officers’ training for the armed forces of the Canada. The article provides information on the existing network of military educational institutions for the officer training of tactical, operational and strategic levels of military command. The terms of officers’ training on tactical, operational and strategic levels have been defined. The analysis of the content of officer training for different armed services of the armed forces and different levels of military administration has been conducted. We used the system of the general scientific methods of theoretical and empirical research, in particular, the theoretical-methodological analysis of the problem and the relevant scholarly resources, systematization and generalization of the scientific information pertaining to the essence and content of the set objectives, monitoring of the existing system of military specialists training in the Armed Forces of the Canada, scientific generalisation, the general scientific methods of logical and comparative analysis, systems approach, peer review, analysis and interpretation of the obtained theoretical and empirical data. An analysis of the concept, structure, goals, content and technologies of officers’ training in the armed forces of the Canada shows that the military education system reflects the current stage of development of the armed forces, as well as the national cultural specificity of the country. Education and training of officers is carried out on the basis of national cultural and military traditions, taking into account the mentality of the Canada people. The main direction of officers’ training is their fundamental military and professional training in both the military and civilian fields. The content of the officers’ training is based on two military education levels. Each level of military education ends with a certain level of qualification. It is possible to distinguish the general tendencies of development of the Canadian military school: improvement of the quality of applicants’ selection, individualization of training of cadets and trainees, stabilization of their number at the present level; further informatization of the educational process, introduction of multimedia learning tools.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0080.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.042
GPT teacher head0.255
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

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