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Record W243065520 · doi:10.21236/ada606211

The Canadian Forces Use of Private Security in Afghanistan: A Consequence of National Decisions

2013· report· en· W243065520 on OpenAlexaboutno aff
Stephen D. Noel

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicMilitary and Defense Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNational securityUse of forcePrivate securityComputer securityBusinessPolitical sciencePublic administrationLawComputer science

Abstract

fetched live from OpenAlex

Since the end of the Cold War, cuts to Canadian defense spending by successive national governments have caused gaps in National Defense. The number of soldiers, particularly those in support trades has decreased. This is concurrent to an increase in the number of tasks, both domestically and internationally that the Canadian Government has given the Department of National Defense. This has given rise to the use of Private Security Companies by the Canadian Forces. The number of Private Security Companies employed by Canada increased in Afghanistan from 2005 to 2011. While there has been a great deal written on the moral, legal and ethical issues associated with using private security to augment the Canadian Forces capability, there has not been a detailed examination of the causes that led to the requirement to use Private Security Companies. The evidence suggests that the augmentation requirement is a natural result of decisions made at the national political level. The value of this study is to increase decision makers understanding of the impact of private security augmentation on Canadian Forces operations in future conflicts. By informing the military, the Canadian Forces can operationalize planning for the use of private security in future conflicts.

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.916
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.128
GPT teacher head0.364
Teacher spread0.236 · 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 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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