Once More to the Well?: Planning for Retirement and Associated Transitions
Bibliographic record
Abstract
The ageing of the population is pressurising frontline health and social service professionals in two respects: demands are increasing need in the population; and expectations for the length of their working life are changing. For some people the prospect of working longer represents an opportunity for continued social connectivity and meaning; for others, it represents continuation of demanding work patterns which do not support health and wellbeing. In this presentation, we explore some potential consequences of moves to postpone retirement and prolong working lives and challenges in forecasting who might benefit from various policy responses. We present data from a survey of 1300 UK social workers who were asked about their perception of late career and retirement, about their levels of wellbeing and their intentions to leave work. The survey contained open text fields in which participants could describe their perceptions in their own words. Plans and expectations around retirement varied greatly across the sample. Many have no immediate plans to retire, with one participant anticipating dropping to “four days per week in my 70s and three in my 80s”, while others had availed of early or flexible retirement schemes. We show patterning in retirement planning by sex, work pattern, area of work and personal circumstances. We found strong associations between some of the reasons identified for retirement and wellbeing indicators in both directions. There was also patterning around the type of organisational provisions which people favoured and those same wellbeing indicators. For example, respondents who favoured retraining for a new role towards the end of their career were more likely to have had sickness absence of up to 20 days in the previous year. We also describe a counterfactual schema for imagining groupings within the population based on the relationship between retirement and wellbeing and test how the data support detection of such groupings. Findings are discussed in terms of the array of policy options available either to government or to employer organisations to safeguard wellbeing on.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".