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Record W2113417739 · doi:10.1177/0963721412438710

Protective Factors for Health Among Low-Socioeconomic-Status Individuals

2012· article· en· W2113417739 on OpenAlexaff
Edith Chen

Bibliographic record

VenueCurrent Directions in Psychological Science · 2012
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocioeconomic statusOptimismPsychologyStressorMeaning (existential)Developmental psychologyGerontologySocial psychologyClinical psychologyEnvironmental healthMedicinePsychotherapistPopulation

Abstract

fetched live from OpenAlex

Low socioeconomic status (SES) is associated with a wide array of poor health outcomes. Nonetheless, some low-SES individuals maintain good physical health despite facing recurrent, severe adversities in life. This article describes a “shift-and-persist” model that explains why that is. The model states that in the midst of adversity, some low-SES children find role models who teach them to trust others, to better regulate their emotions, and to focus on their futures. Over a lifetime, these low-SES individuals may develop an approach to life that prioritizes shifting (accepting stress for what it is and adapting oneself to it) in combination with persisting (enduring life challenges by holding on to meaning and optimism). This combination of shifting and persisting strategies mitigates physiological responses to the barrage of stressors confronted by low-SES individuals and forestalls pathogenic sequelae that lead to chronic disease. Identifying health-relevant protective qualities that naturally occur in some low-SES individuals represents one important approach for improving the health of those who confront a lifetime of disadvantages.

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 score0.138
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.060
GPT teacher head0.440
Teacher spread0.379 · 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

Citations36
Published2012
Admission routes1
Has abstractyes

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