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What do we know about retired physician assistants? A preliminary study

2013· article· en· W1994307503 on OpenAlexaboutno aff
Jennifer Coombs, Roderick S. Hooker, Kimberly D. Brunisholz

Bibliographic record

VenueJAAPA · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PensionGerontologyMedicineSocial securityHealth and Retirement StudyFamily medicinePsychologyDemographyPolitical scienceSociologyLawHistory

Abstract

fetched live from OpenAlex

Retirement generally means the complete end of employment. Retirement is a new phenomenon for physician assistants (PAs), as those trained in the 1970s exit their careers. To better understand retirement patterns of PAs, we undertook a survey in 2011 using a national database. A cadre of 625 respondents met the criteria of being retired and living; the mean age of PA retirement was 61 years (range 47-75 years). Duration of a PA career was 29 years on average (range, 10-40 years). Forty-three percent of respondents retired from family/general medicine and 11% from emergency medicine. Almost all reported receiving Social Security and Medicare; most had some form of a pension. Fewer than one-fifth retired for health reasons. When asked about the timeliness of retiring, 20% wished they had retired later in life; 4% of the men and 7% of the women thought they should have retired earlier; 74% of the men and 73% of the women said they had retired at the right time. Reasons for retiring varied widely. Approximately one-quarter reported volunteering in a medically-related capacity. We suggest that retirement is a concept undergoing evolution in American society and that PAs represent a health profession that reflects the complexity of this evolution.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.005

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 head0.043
GPT teacher head0.278
Teacher spread0.235 · 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.

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

Citations7
Published2013
Admission routes1
Has abstractyes

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