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Record W2768390209 · doi:10.1057/s41266-017-0027-1

An IT outsourcing dilemma at Sick Kids Hospital

2017· article· en· W2768390209 on OpenAlex
Ron Babin, Mohamed Shazadh Khan, Kyle J. Stewart

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 Information Technology Teaching Cases · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsOutsourcingDilemmaBusinessHealth careInformation technologyService (business)Service providerNursingMedical emergencyOperations managementPublic relationsMarketingMedicineEngineeringEconomicsEconomic growthComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This teaching case is based on a true situation at the Hospital for Sick Children, in Toronto Canada. The case asks students to either assume the role of the CIO or to advise the CIO in making a decision to outsource IT at Sick Kids Hospital. The case requires students to understand three important issues: First, while health care costs continue to increase, automation of information is an important opportunity to streamline patient care and reduce costs in a hospital environment. Second, IT outsourcing, relying on external service providers to deliver complex technology services, is a fundamental business strategy across all industries and has great potential in the health care industry. Third, hospitals and health care have unique requirements for IT outsourcing, particularly the critical importance of patient data security and privacy.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.008
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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