Precarity and Aging: A Scoping Review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: The concept of precarity holds the potential to understand insecurities and risks experienced by older people in the contemporary social, economic, political and cultural context. This study maps existing conceptualizations of precarity in relation to aging and later life, identifies key themes, and considers the use of precarity in two subfields. RESEARCH DESIGN AND METHODS: This article presents the findings of a two-phase scoping study of the international literature on precarity in later life. Phase I involved a review of definitions and understandings of precarity and aging. Phase II explored two emerging subthemes of disability and im/migration as related to aging and late life. RESULTS: A total of 121 published studies were reviewed across Phase I and Phase II. Findings reveal that the definition of precarity is connected with insecurity, vulnerability, and labor and that particular social locations, trajectories, or conditions may heighten the risk of precarity in late life. IMPLICATIONS AND DISCUSSION: The article concludes by outlining the need for conceptual clarity, research on the unique multidimensional features of aging and precarity, the delineation of allied concepts and emerging applications, and the importance of linking research results with processes of theory building and the development of policy directives for change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".