PRODUCTIVE AND ACTIVE RURAL AGING: TOWARD CRITICAL PERSPECTIVES
Bibliographic record
Abstract
Abstract Despite global trends in rural population ageing, relatively little attention within research and policy has been directed to understanding what it means for rural people, communities and institutions to be at the forefront of twenty-first century demographic change. To build understanding of rural ageing, this symposium draws together papers from four countries to provide insights in the gaps in rural ageing research – specifically the in context of productive and active rural ageing by examining rural work, retirement and volunteering through the critical perspectives of citizenship, contestation and complexity. Winterton and Warburton will explore how active citizenship trends among rural older adults support or hinder the capacity of rural settings to support health ageing. Colibaba and Skinner will discuss the contestation of rural ageing by examining a volunteer-based rural library and the emergent ‘contested spaces of older voluntarism’ whereby older volunteer negotiate their rights and responsibilities associated with ageing and volunteering in rural communities. Duvvury and Ni Leime will examine the interactions between the twin phenomena of feminisation of agriculture and the feminisation of ageing in the consequent implications for rural women’s work and retirement. Skinner and Joseph offer a critical perspective on voluntarism in ageing rural communities by examining volunteer leadership biographies as another means of understanding the contribution of older rural adults.
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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 | 0.036 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.015 | 0.059 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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".