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Record W2948318473 · doi:10.35467/sdq/109259

The royal military college of Canada: Responding to the call for change

2019· article· en· W2948318473 on OpenAlexafffundabout
Harry J. Kowal

Bibliographic record

VenueSecurity and Defence Quarterly · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary, Security, and Education Studies
Canadian institutionsRoyal Military College of CanadaRoyal Ottawa Mental Health Centre
FundersMinistère de la Défense NationaleCanadian Armed ForcesCanadian Defence AcademyStrong
KeywordsOfficerExcellencePolitical scienceWork (physics)ParliamentManagementPublic relationsLawEngineeringPolitics

Abstract

fetched live from OpenAlex

<i>The Royal Military College of Canada (RMC) has a very proud history of producing quality officers for over 140 years, delivering excellence in education, research and military training that is responsive to the needs of Canada, the Defence community and the ever-changing global security environment. RMC is unique as it is a military unit that is also a recognized university. The primary mission of RMC is to support the Regular Officer Training Plan (ROTP) by educating, developing and inspiring bilingual and fit, ethical leaders to serve the Canadian Armed Forces (CAF) and Canada with distinction. Since RMC opened its doors in 1876 to the fi rst 18 cadets, there have been a number of studies that have examined the RMC program and that have been the catalyst for positive change. T ese pivotal moments in history have been indispensable for RMC to remain relevant and continually improve. Of late, there has been a significant amount of attention placed on RMC again, defi ning another pivotal moment in RMC’s history that has become the catalyst for change once again. In October 2016, the Chief of the Defence Staff (CDS), General Jonathan Vance, initiated a Special Staff Assistance Visit (SSAV) to ensure the high standards expected of RMC are upheld and the Auditor General (AG) of Canada, Mr. Michael Ferguson, completed an audit of the ROTP at RMC, the results of which were presented to Parliament in November 2017. Many changes are already in place, but there is more work to do. With a look at governance, the four-pillar program and the call for change, this paper outlines what steps RMC has and will be taken to posture this ‘university with a difference’ for success for years to come.</i>

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2019
Admission routes3
Has abstractyes

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