MétaCan
Menu
Back to cohort
Record W1212734513

Reinsuring Health: Why More Middle Class People Are Uninsured and What the Government Can Do

2010· article· en· W1212734513 on OpenAlexaboutno aff
David A. Cather

Bibliographic record

VenueJournal of Risk & Insurance · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Health carePublic healthQuarter (Canadian coin)Face (sociological concept)Middle classPolitical scienceBusinessPublic administrationSociologyMedicineLawHistoryNursingSocial science
DOInot available

Abstract

fetched live from OpenAlex

Reinsuring Health: Why More Middle Class People Are Uninsured and What the Government Can Do, by Katherine Swartz, 2006, Russell Sage Foundation, New York, pp. 203. ISBN: 0-87154-787-2 In 2008, the number of nonelderly Americans without health insurance approached 47 million people, with millions of others concerned that a faltering economy may increase their chances of losing their own health care coverage. As the United States considers a variety of alternatives to decrease the ranks of the uninsured, Katherine Swartz offers a timely book on how the face of the uninsured has dramatically changed over the past quarter century and provides a thoughtful proposal for improving how health insurers can better address this crisis in coverage. In Reinsuring Health, Swartz examines whether a public-private health care reinsurance model can be implemented on a national level, designed as a program in which the federal government assumes the role of the reinsurer of catastrophically high health care risks. Reinsuring Health is divided into three broad sections: a comparison of how the face of the uninsured have changed from 1979 to 2004, a description of how the individual and small-group health insurance markets currently operate, and final proposal for a new public-private structure that may make private health insurance more affordable. Swartz, a professor of health policy and management at Harvard's School of Public Health, has thus written a scholarly book that covers a lot of ground, but in an accessible style that a nonacademic authence can fully appreciate. One of the clear strengths of Reinsuring Health is its description of how the population of Americans without health care in 1979 is radically different from the uninsured population today. In 1979, nearly 40 percent of the uninsured in the United States were children living in low-income families, a statistic that prompted the creation of a variety of public programs (e.g., the State Children's Health Insurance Programs, changes in Medicaid) that were designed to reduce this percentage. By 2004, these programs, combined with shifts in demographics and birthrates, had reduced the percentage of the iininsured population consisting of children by half. In their place, the profile of Americans without health insurance today is much more diverse, and often from families earning middle-class incomes. To explain how these differences occurred, Swartz provides a thorough summary of an extensive literature that documents how a variety of recent employment trends - e.g., outsourcing, the declining influence of labor unions, the growing ranks of the self-employed, replacing employees with independent contractors and contract employees, and an evolving job market that consists of fewer employees from large manufacturers and more employees from smaller service firms - have resulted in a larger fraction of the workforce holding jobs without employer-sponsored health care. As a result of these changes in the workforce, 40 percent of the uninsured today are between the ages of 25 and 44, and 30 percent come from a family with income above the national median. Thus, unlike 1979, the factors that have resulted in a significant number of uninsured people today are not tied as closely to unemployment and poverty but are increasingly attributable to conscious decisions by employers to pare down the portion of their workforce that is eligible for expensive benefits like group health insurance. In the second section of Reinsuring Health, Swartz describes how the individual and small-group health insurance markets operate. Chapter 3 explains why health insurance provided through an employer group generally costs less per person than health insurance through individual policies. Next, drawing heavily from the work of Klein (2003), the chapter chronicles the events that have led to U.S. employers becoming the first-line providers and financiers of health insurance. The remainder of the chapter explains why large employers are able to offer health insurance to their workers at a lower cost than small employers, focusing on large-firm economies of scale and their ability to spread the costs of adverse selection across a large group of employees. …

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)0.002
metaresearch head score (Gemma)0.000
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 score0.263
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.241
Teacher spread0.212 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Risk & InsuranceSame topicHealthcare Policy and ManagementFrench-language works237,207