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Record W2897987082 · doi:10.11575/prism/33132

Falling short: suboptimal outcomes in Canadian defence procurement

2018· dissertation· en· W2897987082 on OpenAlexaboutno aff
Ian C. MacMillan

Bibliographic record

VenuePRISM (University of Calgary) · 2018
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFalling (accident)ProcurementOperations managementBusinessForensic engineeringOperations researchAeronauticsEngineeringMedicineMarketingEnvironmental health

Abstract

fetched live from OpenAlex

Why do Canada’s military procurement projects often fall short of their primary goals? Otherwise known as a suboptimal result, defence acquisitions regularly fall short of established delivery schedules, accruing cost-overruns, sometimes resulting in cancellation of key materiel. One-hundred percent of the twenty-five Major Crown Projects at the Department of National Defence have experienced delays in achieving key milestones. Aside from cost, suboptimal results are injurious to Canada’s tri-force military. Fortunately, the matter has not gone unchecked. A fairly recent surge in procurement research has generated a critical mass of Canadian-focused literature. Preliminary research for this study shows a connection between suboptimal results and the organizations and personnel that populate procurement processes. Based on the bureaucratic politics model, a competitive interaction between uniquely conditioned policy players causes suboptimal delays and costs. Players orient outcomes to suit personal and organizational interests. The advantage of the bureaucratic politics model is the clarity with which it illustrates decision processes. Its simplistic structure serves as an ideal model for comparing three cases in Canadian procurement. Taken from the Department of National Defence’s Status Report on Transformational and Major Crown Projects, this study tests the bureaucratic theory against the Tank Replacement Project, the Joint Support Ship Project, and the ongoing project(s) to replace Canada’s CF-18 Hornets. The objective is to see if these cases share common findings contributing to suboptimality. The bureaucratic model assists the methodological goal of a structured, focused comparison. Two of the three cases demonstrate the competitive interaction between players as a factor in determining delays and cost-overruns. Although the Joint Support Ship Project included a host of unique players competing to determine decision outcomes, the factor that contributed to schedule slippage was the result of widespread agreement on a build in Canada approach. This consensus led to reliance on one underequipped shipyard to approach an overambitious project. Based on the overall study, three findings prevail. First, reports by bureaucratic institutions like the Parliamentary Budget Office and the Office of the Auditor General have tremendous political capital. Second, domestic production schemes are noble, but sometimes unrealistic. Third, competition for goods is always necessary.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.026
GPT teacher head0.219
Teacher spread0.192 · 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 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
Published2018
Admission routes1
Has abstractyes

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