MétaCan
Menu
Back to cohort
Record W7065798022

Features of Physical Training for Officers in Military Educational Institutions in Canada

2022· article· uk· W7065798022 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy · 2022
Typearticle
Languageuk
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Government (linguistics)Work (physics)On-the-job training
DOInot available

Abstract

fetched live from OpenAlex

Introduction. The activities of the State Border Guard Service of Ukraine are taking place in a challenging military-political situation. Under these conditions, the quality and intensity of physical training of border guard officers takes on special significance, since they are required to be hardy, capable of enduring a variety of physical and psychological stresses. In order to find effective ways to solve the problems of physical training of officers of the State Border Guard Service of Ukraine, it is important to study the experience of training military officers in NATO member countries, in particular Canada. Purpose of this article is to investigate and highlight the features and organizational and pedagogical foundations of officers' physical training in military educational institutions in Canada. Methods. The methods of analysis, generalization, comparison and systematization were used to achieve the goal of the study. The source base is the information contained in the official websites of Canadian military education institutions. Results. The physical training organization at the Royal Military College of Canada has shown that its educational program offers exceptional opportunities to develop the potential of cadets-athletes. The athletic component is one of the four components of officer training at the Royal Military College of Canada. The physical training program is designed to provide all future officers with the opportunities to participate in physical activities and sports that require exertion in order to develop their general capabilities, self-confidence and leadership. The goal of the program is to improve the physical fitness of cadets; develop leadership capabilities; create a competitive environment; introduce cadets to different sports; develop team spirit; promote an active and healthy lifestyle. During training, cadets are tested on their physical fitness through a fitness test conducted twice a year. Originality. Scientific novelty lies in the further development of scientific ideas about the organizational and pedagogical foundations of the organization of physical training in educational institutions of NATO countries. The results will contribute to the formation of methodological recommendations to the organizers of physical training to improve its quality. Hence the practical significance of the results of the study. Conclusion. The quality of physical training in Canada’s military colleges is ensured by qualified physical education and sport professionals; high level of physical fitness of applicants for entering military colleges; a significant amount of time in the educational program for physical training and sports; modern sports facilities; a set of measures to create motivation for physical activity and sports. A necessary element of physical training is testing that determine eligibility for further study in military schools and service in the armed forces.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.078
GPT teacher head0.323
Teacher spread0.245 · 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 designObservational
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueThe Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogySame topicAstrophysical Phenomena and ObservationsFrench-language works237,207