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Record W1975130557 · doi:10.5430/jha.v4n2p23

Preliminary development of a reference conceptual framework about social responsibility of public hospitals in China

2015· article· en· W1975130557 on OpenAlexvenueno aff
Lizheng Shi, Fei Liang, Hui Shao, HU Xian-zhi, Qian Gu, Wenbin Liu, Xiong Ke, Thomas Jefferson Stranova, Yingyao Chen

Bibliographic record

VenueJournal of Hospital Administration · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsDelphi methodCorporate social responsibilitySocial responsibilityChinaQuality (philosophy)Public relationsBusinessHealth carePolitical scienceComputer science

Abstract

fetched live from OpenAlex

Public hospitals play an integral part in the health, welfare, and success of the communities they serve. In their roles, public hospitals are expected to embrace the principles of social responsibilities, but these ideas are often vaguely or poorly defined or implemented in the healthcare setting. This paper uses China as a case study to develop a theoretical framework of social responsibilities for public hospitals that can be applied to evaluate hospital performance on social responsibility and to enhance health management educational programs. A systematic literature review and Delphi panel of Chinese domestic scholars were used to examine potential indicators to measure social responsibilities of public hospitals. A four-level of corporate social responsibilities (CSR) framework was combined with four performance parameters for medical institutions (accessibility, appropriateness, quality, and efficiency) to create a matrix structure of social responsibilities with empirically studied indicators.

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)0.004
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.059
GPT teacher head0.311
Teacher spread0.251 · 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 designObservational
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

Citations1
Published2015
Admission routes1
Has abstractyes

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