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Record W3047286424 · doi:10.12927/hcq.2020.26276

A Post-Merger Value Realization Framework for a Large Community Hospital

2020· article· en· W3047286424 on OpenAlexaffvenue
Christa Hruska, Alfred Ng, Michele James, Cedomir Tosevski

Bibliographic record

VenueHealthcare Quarterly · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsContinental (Canada)Sheridan College
Fundersnot available
KeywordsRealization (probability)Value (mathematics)Key (lock)Process managementBusinessTracking (education)Operations managementKnowledge managementComputer scienceSociologyEngineeringComputer security

Abstract

fetched live from OpenAlex

To capture the value of the Scarborough Health Network amalgamation, a value realization framework (VRF) was developed, based on three themes and nine goals. Each goal was mapped to key strategies and indicators that signalled our delivery of value to the community. Value was achieved when indicators moved in the desired direction. The VRF acknowledged that integration is a journey and identified value in the short, medium and long term. Four quarterly VRF progress reports were completed, illustrating a positive story of the post-merger period. The VRF provided a standardized framework for tracking and monitoring strategies for a successful organizational transition.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0130.012
Scholarly communication0.0180.012
Open science0.0040.009
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.102
GPT teacher head0.454
Teacher spread0.351 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2020
Admission routes2
Has abstractyes

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