Narratives of transition on ageing and late life
Bibliographic record
Abstract
This chapter marks the beginning of Part Two, exploring transitions as contested terrain in late life. Building on the foundations established in Chapters Two to Five, the second part of the book uses the illustrative experiences of older people to reconsider knowledge about transitions and the lifecourse. The interviews presented in this chapter highlight how contemporary trends and dominant views articulated in the academic literature, the socio-cultural context and policies related to age might be rethought. Drawing attention to older people's narratives exemplifies a critical practice of gerontology grounded in the lifecourse. Taking narrative interviews into account represents a move from fixed interpretations of age to more fluid accounts that may simultaneously correspond with and challenge, current conceptions of late life. Chapter Six presents nine case illustrations organised in relation to success-based models, ageing and decline, and varying social locations. Chapter Seven draws these interviews together, exploring questions that challenge dominant understandings of transition articulated in the first section of the book. Chapters Eight and Nine pick up on the specific issues of diversity and the polarisation of health and illness that may affect interpretations of transition in relation to late life. Chapter Ten draws together insights and raises questions that extend beyond the focus of this book. The current chapter considers nine case studies that draw attention to older people's interpretations and expectations of growing old. It highlights variations that exist between accounts, and explores normative expectations alongside the atypical means that older people may use to make sense of transition in late life. For example, older people's life stories may reflect the expected transition types such as retirement or widowhood or age- or stage-based assumptions, or make use of dominant discourses such as activity or productivity to frame their experience. At the same time, however, their experiences and interpretations may differ from or challenge the taken-for granted knowledge and expectations, especially where age, relationships and diversity are considered. This chapter does not present older people's experiences as more ‘authentic’ voices, but rather considers their accounts as alternative understandings based on lived experience. Likewise, the accounts are not intended to articulate arguments related to identity that are explored elsewhere. While identity is one aspect of this experience, it is not the sole basis for the argument.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".