Peculiarities of the Application of Information and Communication Technologies for Distance Learning of the Canadian Border Guard Service Personnel
Bibliographic record
Abstract
The paper reveals the peculiarities of the development of distance education in Canadian educational institutions. The specifics of distance learning in the most popular land-based and virtual universities in different provinces of Canada are highlighted. The main tasks of distance education in the Canadian higher education system are identified. The key problems that hinder the development of distance education at the international level are identified. It is proved that distance learning in Canada is successfully integrated into the educational process and is aimed at training highly qualified specialists in various fields. It is known that due to changes in security legislation in 2001, the practice of visiting different checkpoints was cancelled. It is proved that Second Life is an online world in which users (residents) create avatars and interact with other participants, places or objects. It was noted that a virtual border crossing point was created using Second Life to train cadets to conduct interviews with people crossing the border at checkpoints to Canada. It has been researched that in order to enroll in distance learning and continuing education courses, certain requirements must be met. It is indicated that distance education offers hundreds of courses available on a monthly or semester basis. The article describes the distance learning course "Border Services" on the website, which is divided into two parts. It is known that the first part of the course is designed to provide students with an understanding of the activities and functions of the Canada Border Services Agency and the second one is to provide students with an understanding of Canadian citizenship and immigration.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".