Bibliographic record
Abstract
Globally, while the population is ageing, only 3% of older (≥65 years) adults are engaged in entrepreneurship. The Healthy Ageing agenda is responding to the population trends by increasing its focus on elements of active or productive ageing (incorporating older working) with quality of life as a primary outcome. Alignment and exploitation of the synergies between healthy ageing and older entrepreneurial engagement are lacking. Entrepreneurship education is broadening its focus and targeting inclusivity, albeit with as yet little focus on the older population. Older entrepreneurship, while tentatively linked with increased quality of life, has yet to receive direct attention in the healthy ageing literature, perhaps in part due to the lack of empirical evidence supporting healthy ageing outcomes directly associated with older entrepreneurial skills training or entrepreneurial endeavours. Limited data supports the engagement of people at or beyond retirement age in entrepreneurship and there is little understanding about this cohort’s needs and drivers for entrepreneurial skills training. This “Smart Ageing and Renewal through Entrepreneurial Skills Training” developed research programme provides ground-breaking exploratory work to address current knowledge gaps in entrepreneurial education for adults over 65 years. This study asks what concepts and individual facets have the potential to inform older healthy ageing aligned entrepreneurship as well as aligned bespoke older entrepreneurial skills training? A cross-disciplinary, conceptual alignment between the healthy ageing and older entrepreneurship domains was conducted, with twenty healthy ageing concepts identified as common to both literatures. The study then explores the identified aligned concepts in practice. Following an action research framework, this study first sought key stakeholder feedback on the suitability of existing processbased entrepreneurial education materials for older individuals. Suitable aligned measurement constructs for entrepreneurial skills training evaluation in the cohort were then identified and suitable measures for facets of older entrepreneurship were validated in an over 65s population. Aligned measures included: EuroQoL 5D-5L quality-of-life measure, CASP12 and ICECAP-O wellbeing measures, Montreal Cognitive Assessment (MoCA) and BRS6 resilience measure, total entrepreneurial competences, entrepreneurial activity level and entrepreneurial self-efficacy. The research programme next implemented practical testing of these aligned measures. This was achieved through sampling in the general older population (n=102) to establish existing cross-domain relationships between healthy ageing and older entrepreneurship measures and by a collaborative, inclusive feasibility pilot study of stakeholder-approved entrepreneurial skills training provision in a community setting. Promising relationships were identified between healthy ageing outcomes of quality of life, wellbeing and resilience and those of entrepreneurial competences and self-efficacy, with total entrepreneurial competence explaining 21% of the variance in the CASP12 wellbeing measure, (R2 change 0.21, Fchange (5,.90)= 8.03, p
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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 | 0.005 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".