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Record W2138136185 · doi:10.1177/002214650704800205

The Life-Course Origins of Mastery among Older People

2007· article· en· W2138136185 on OpenAlexaff
Leonard I. Pearlin, Kim B. Nguyen, Scott Schieman, Melissa A. Milkie

Bibliographic record

VenueJournal of Health and Social Behavior · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsCanadian Institute for Health Information
FundersNational Institute on Aging
KeywordsStatus attainmentPsychologyStressorAffect (linguistics)Life course approachDevelopmental psychologyEducational attainmentSense of controlMastery learningSocial psychologyGerontologyClinical psychologyDemographySocioeconomic statusSociologyMedicine

Abstract

fetched live from OpenAlex

In this article, we aim to identify the sources of mastery--the understanding that individuals hold about their ability to control the circumstances of their lives. The sample for our inquiry was drawn from the Medicare beneficiary files of people 65 and older living in Washington, DC, and two adjoining Maryland counties. We find that past circumstances, particularly those reflecting status attainment and early exposure to intractable hardships, converge with stressors experienced in late life to influence elders' level of mastery. The impact of past conditions, however, does not necessarily directly affect the current mastery of older people. Instead, the effect of prior experiences on current mastery is mediated by what we refer to as life-course mastery: one's belief that one has directed and managed the trajectories that connect one's past to the present. Our analyses show that life-course mastery largely serves as the mediating channel through which individuals connect their past to their present.

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)0.005
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.389
Teacher spread0.356 · 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

Citations221
Published2007
Admission routes1
Has abstractyes

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