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Record W2036655619 · doi:10.4018/jebr.2007100104

Evolving E-Health System Symbiosis

2007· article· en· W2036655619 on OpenAlexaffabout
Denis H.J.

Bibliographic record

VenueInternational Journal of E-Business Research · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSoftware deploymentInformation and Communications TechnologyKnowledge managementRealmWitnessCorporate governanceInformation systemPublic relationsHealth careInformation technologyConceptual frameworkBusinessSociologyPolitical scienceEngineeringComputer scienceSocial science

Abstract

fetched live from OpenAlex

The 21st century continues to witness the transformation of organizational systems globally through the deployment of information and communication technologies (ICT). The emerging future is witnessing the convergence of artificial intelligence, biotechnology, nomadic information systems, and nano-technology. This promises to further compel inter-organizational and inter-sectorial interactive transformations. The health care sector is no exception to the inter-organizational dynamic imperatives driven with ICT innovative advances. This article proposes a conceptual model of symbiotic e-health networks in a meta-cultural domain that goes beyond the realm of extant literature on dyadic relationships. The model dimensions are posited on a key informant approach and content analysis of the strategic perceptions of international ICT and health care executives interacting through dyadic partnerships. The findings and implications of the study for the model and further information management research are underscored. The underlying meta-cultural frame is characterized by public governance values and the article explores its perceived role in sustaining symbiotic e-health networks in Canada and Sweden.

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)0.007
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0020.000
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 head0.159
GPT teacher head0.421
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2007
Admission routes2
Has abstractyes

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