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Record W2023705796 · doi:10.4018/jgim.2009070104

Understanding IT Governance

2009· article· en· W2023705796 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Global Information Management · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCorporate governanceCLARITYBusinessShareholderAccountingLegislationPublic relationsFinancePolitical scienceLaw

Abstract

fetched live from OpenAlex

Legislators, regulators, and shareholders increasingly demand good governance over all aspects of their business. While much is made of financial governance, most legislation and regulation implicitly recognizes the need for prudent governance of information technology (IT) functions. In this study we conduct an exploratory collective case study of IT governance (ITG) in two financial mutuals–one in Australia and one in Canada--using a contextual lens. In one case, the mutual governs its IT through Board participation in a subsidiary. In the second, governance is delegated to management and a lead director. Both of these mechanisms appear to minimize ITG risk, and are the result of their respective regulatory environments. This research begins to lend some clarity regarding IT governance choices by firms, and denotes important contextual differences between countries’ regulatory environments. This will allow researchers, managers, and directors to better understand and discriminate between ITG processes and structures.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.004
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 head0.030
GPT teacher head0.233
Teacher spread0.204 · 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