Ageing and Community: Introduction to the Special Issue
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Population ageing is one of the major contemporary issues facing societies across the world. Originally framed as a major social and economic challenge, demographic ageing is now beginning to be seen as offering huge potential to individuals as well as to their communities. It is this positive potential that we explore in this issue by utilising two key disciplinary approaches—social gerontology and social/community psychology. In this introduction, we argue that focus on only one or the other of these perspectives is limiting. Instead, a more critical approach is needed that incorporates the strengths of both disciplines in order to build a more complete and stronger understanding of ageing and community. Thus, a focus on social gerontology highlights ageing issues and explores the diversity of older people and their interactions with community. By incorporating a social/community psychology approach, there is potential to complement this body of work through a deeper level of analysis around community, as well as individual and relational dimensions. The result is a special issue that brings together these two perspectives to address some of the shortcomings of approaching ageing through solely one disciplinary lens. Copyright © 2013 John Wiley & Sons, Ltd.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it