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Record W2341044418

Security and Planning: A Canadian Case Study Analysis

2013· dissertation· en· W2341044418 on OpenAlexaboutno aff
Giuseppe Bartolo

Bibliographic record

VenueUWSpace (University of Waterloo) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceGeographyEnvironmental planning
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores security planning policy in Canada. It provides a historical overview of the securing of cities from the threat of mass violence and demonstrates how violence affects urban populations and the form and function of cities as a result. A purposefully stampeded case study approach is used to determine the state of security planning in Canada and compare selected cities to a benchmark case of Washington D.C. This thesis contributes to the understanding of security planning within Canada in the post September 11, 2001 world and offers insight into strategies used in defense of urban areas The review of literature and discussion sections also provide a critical assessment of security planning which has occurred in the time following WWII, the IRA crisis in Britain the FLQ crisis in Quebec and the terrorist attacks in London and New York in the past decade. Research questions are answered through a case study and literature analysis approach. Results demonstrate that American responses to the threat of terrorism have motivated various governmental agencies to create policy and physical responses to respond to the threat of terrorism. This thesis concludes that Canada, in comparison to the United States and other areas has done little to secure itself against terrorist attack and more specifically that urban planning and municipalities in Canada have done little to integrate anti-terrorism security planning into their planning policy. It is argued that a lack of federal mandates, a lack of motivation and education in planning spheres as well as funding issues are contributing factors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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