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Record W1548032922

DETERMINING IT TCO: LESSONS AND EXTENSIONS

2001· article· en· W1548032922 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLife Cycle Costing Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsTotal cost of ownershipExtant taxonExternalityBusinessTotal costRisk analysis (engineering)Cost accountingIndustrial organizationEnvironmental economicsComputer scienceEconomicsMicroeconomicsAccounting
DOInot available

Abstract

fetched live from OpenAlex

All resources need to be managed to realize opportunities. Isolating the benefits of Information Technology and relating them to the associated costs has proved elusive and threatened emerging opportunities. A change of approach has been advocated to overcome these problems which focuses on the Total Cost of Ownership. Over the past several years, the Total Cost of Ownership has been both hailed and scorned. The origins of the Total Cost of Ownership and its development provide the foundation for inquiry. The advantages and disadvantages of this cost measure are discussed from the extant management literature. Current usage of the Total Cost of Ownership is examined. Considerations of capacity levels, opportunity costs, and positive and negative externalities are introduced to focus on cost containment issues. The assessment identifies the pitfalls and opportunities in using the Total Cost of Ownership to ascertain the costs of Information Technology. 1.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.057
GPT teacher head0.277
Teacher spread0.219 · 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

Quick stats

Citations1
Published2001
Admission routes1
Has abstractyes

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