BABY-BOOMERS’ VOLUNTEERING IN NON-PROFIT ORGANIZATIONS OFFERING HOME SUPPORT
Bibliographic record
Abstract
Non-profit organizations, important actors in the field of home support, are facing challenges such as recruiting and retaining volunteers. In view of the ageing population, this situation is worrisome: these organizations essentially rely on volunteer action. The imminent wave of baby-boomers entering retirement may improve the situation. However, free time and volunteering are not synonymous. This poster will report the findings of a study which sought: 1) to identify individual and organizational factors that facilitate and/or hinder baby-boomers’ volunteering in non-profit organizations; 2) to better understand the interactions between them; and 3) to create a model of baby-boomers’ volunteering. This descriptive and comprehensive study is based on qualitative methods and a contemporary Straussian grounded theory approach, and is guided by an integration of the Bronfenbrenner’s ecosystemic approach and the volunteer process model. The theoretical sample consists of 34 participants: volunteers, non-volunteers and volunteer coordinators. Semi-structured interviews are conducted and supplemented by non-technical literature. For each stage of the volunteering process (antecedents, experiences, consequences), individual factors (e.g.: knowledge, availability, capacities, motivations) and organizational factors (e.g.: mission, activities, organizational structure, support) represent barriers and/or facilitators according to their intervention context. Some factors play a key role at a specific moment, while others appear transverse to the volunteering process. However, individual and organizational factors do not act alone; they interact with interpersonal and social factors. Despite the benefits associated to volunteering, it is important to remain critical concerning its promotion. Pernicious shifts may happen such as a normalization and an instrumentalization of volunteering.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".