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Record W560668078 · doi:10.1017/cbo9780511763151

New Frontiers in Resilient Aging

2010· book· en· W560668078 on OpenAlexaff
P. S. Fry

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsOpenness to experienceSocial connectednessPsychologyVitalityPsychological resilienceCoping (psychology)PessimismSuccessful agingAging in placeCognitionCognitive declineGerontologySocial psychologyClinical psychologyDementiaMedicine

Abstract

fetched live from OpenAlex

A typically pessimistic view of aging is that it leads to a steady decline in physical and mental abilities. In this volume leading gerontologists and geriatric researchers explore the immense potential of older adults to overcome the challenges of old age and pursue active lives with renewed vitality. The contributors believe that resilience capacities diminishing with old age is a misconception and argue that individuals may successfully capitalize on their existing resources, skills and cognitive processes in order to achieve new learning, continuing growth, and enhanced life-satisfaction. By identifying useful psychological resources such as social connectedness, personal engagement and commitment, openness to new experiences, social support and sustained cognitive activity, the authors present a balanced picture of resilient aging. Older adults, while coping with adversity and losses, can be helped to maintain a complementary focus on psychological strengths, positive emotions, and regenerative capacities to achieve continued growth and healthy longevity.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.006
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0150.005

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 head0.017
GPT teacher head0.273
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations75
Published2010
Admission routes1
Has abstractyes

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