MétaCan
Menu
Back to cohort
Record W2782809622 · doi:10.3968/10065

The Relationship Between the Basic Medical Insurance and the Commercial Medical Insurance in the Old Age Security in China

2017· article· en· W2782809622 on OpenAlexvenueno aff
Lai Guo-yi

Bibliographic record

VenueCanadian social science · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedical insuranceActuarial scienceReimbursementPoint (geometry)Insurance policyMedical underwritingKey person insuranceChinaBusinessCasualty insuranceGroup insuranceGeneral insuranceSecurity systemEconomicsIncome protection insuranceHealth careComputer scienceComputer securityLawEconomic growthPolitical scienceMathematics

Abstract

fetched live from OpenAlex

It is very significant to explore the interacting relationship between the basic medical insurance and commercial medical insurance for improving the medical security system. Based on the analytical framework of expected utility theory, by analyzing the model of insurance demand theory, this article shows following: the interacting relationship between the basic medical insurance and commercial medical insurance is either “Complementary Effect ” or “Crowd-out Effect”. The dominant relationship is decided is depend on the probability of illness in the elderly and the setting rate of basic medical insurance reimbursement. When both medical insurances coexist, if both price and quantity of commercial medical insurance reach the optimum point, the expect utility of the medical security for the aged will maximize.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.067
GPT teacher head0.314
Teacher spread0.247 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCanadian social scienceSame topicHealthcare Policy and ManagementFrench-language works237,207