Bibliographic record
Abstract
Introduction The purpose of this chapter is to establish and describe the critical human ecology lens that challenges assumptions about growing older in rural areas. This lens is an essential element of the book in which we consider the interactions of older adults with the rural contexts that shape their experiences. Rural communities incorporate many elements of diversity that influence the lives of older adults: climate, landscape, distance from family networks, availability and access to services, migration patterns, community economic viability, age, gender roles and relationships. In this chapter we establish the structure and overall approach to the book, presenting the overall goals of the book and how the chapters address these goals. Throughout, we address the question: ‘Are rural communities good places to grow old?’. Considering the ‘rural’ in rural ageing The title of this book, Rural ageing , reflects our guiding assumption that experiences of ageing are diverse, and that understanding this diversity requires an expanded consideration of ageing in various contexts. Rural is one such context. As Bonnie Dobbs and Laurel Strain note in Chapter Nine, a substantial proportion of the world's population lives in rural areas – from approximately 25% in North and South America to more than 60% in Africa and Asia. Older adults are over-represented in these rural places and their proportion of the population is growing faster than in urban areas (Hart et al, 2005; Statistics Canada, 2007a). Increasing importance is attached to the geographies of rural areas (Cloke et al, 1997; Friedland, 2002), challenging views of hinterlands bereft of opportunity and socially and culturally lagging (Wiebe, 2001) or of idyllic pastoral settings (Bell, 1997). Such unidimensional views of rurality leave little scope for understanding the variety of rural places. Furthermore, older adults have often been made invisible by ‘predominantly male, white, middle class, middle-aged, straight and able-bodied’ views of rural residents (Cloke et al, 1997, p 211). We expand these rural discourses through our focus on the lives of a variety of older adults in diverse rural surroundings. There are a number of ways in which one can understand rurality, and definitions have been the subject of much debate. However, they can be broadly categorised within two approaches. These are rural as a distinctive type of locality and rural as a social representation (Halfacree, 1993; Atkin, 2003).
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".