On the track of evaluated programmes targeting the social participation of seniors: a typology proposal
Bibliographic record
Abstract
ABSTRACT Nowadays, the social participation of seniors represents a central challenge for both individuals and collectivities. The participative perspective is indeed present in most of the contemporary discourses on ageing, and is viewed both as a way to manage the current demographic juncture and as a promising direction for enhancing seniors’ wellbeing and achievements. This article examines 32 programmes aimed at fostering the social participation of seniors that were both implemented and evaluated, and whose results were published between January 1970 and August 2011. Based on each programme's approach, a typology of social programmes is proposed. The programmes are grouped in five categories, ranging from programmes offering an individualised approach to socio-political programmes. Classification is based on the various ways the concept of social participation is defined and acted upon by the reviewed programmes. Far from being neutral, each category suggests a specific representation of the social roles of seniors. In addition, the paper discusses how the proposed typology can guide both policy and practice, linking identity and agency issues to organisational and structural considerations. Three uses for the typology are suggested: as a policy-making support, as an evaluative framework, and as an experimental space for community practice.
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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 | 0.033 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".