“What’s Age Got to do With It”: an Examination Into the Developments Within the Field of Subjective Views on Aging
Bibliographic record
Abstract
Various life circumstances lead to great variability in how individuals perceive themselves as they age. Subjective Views of Aging: Theory, Research, and Practice expands on differing experience and perspectives while building on an earlier volume (Diehl & Wahl, 2015) that left areas to be explored, which the current collection addresses. As such, Subjective Views of Aging focuses on theoretical advancements, empirical research settings, and methods of recent years. The book is divided into three sections. Our review considers each section with an eye toward next steps for gerontology and the vast disciplinary fields that will benefit from a better understanding of subjective aging. Recent theoretical contributions on subjective views on aging (VOA) center on how stereotypes are perceived internally and societally as we age. Many of the chapters within this section use common social science stereotype frameworks to theorize how individuals might craft ideologies about aging. For example, Chapter 3 addresses stereotype embodiment, placing reasonable parameters around considerations of the self and how stereotype embodiment relates to later life stigma. Chapter 4 delves into how expectations of aging affect how people are expected to act and behave. Chapter 6 builds on these theoretical frameworks with the inclusion of gender as a central determinant of aging experiences. The important notion of intersectionality continues within Chapter 8 as the authors examine how individuals’ perception of their aging process is culturally guided. Overall, despite theoretical advances, this section points to the need for more work to be done, especially with regards to identities and how they might play a role in subjective VOA.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".