Understanding Constraints Younger Youth Face in Engaging as Volunteers
Bibliographic record
Abstract
Many nonprofit organizations needing volunteers struggle to find individuals who can provide the hours of support their programs, services, and events need (Urban Institute, 2004). Researchers have recognized the contribution of youth volunteers and have examined various aspects of youth volunteer experiences to better understand them (e.g., Hall, McKeown, & Roberts, 2001). Much of the research has focus on those 13 and older, however, youth between the ages of 8 and 12 (younger youth) have been overlooked. Research shows that younger youth do volunteer (Grimm, Dietz, Spring, Arey, & Foster-Bey, 2005), but little is known about the experiences they have. The purpose of this study was to explore constraints younger youth face and ways in which these constraints are negotiated. Using semi-structured, face-to-face interviews, data were collected from 73 youth volunteers (31 males; 42 females) ages 8 to 12 and 7 Executive Directors from Boys and Girls Clubs (BGC) in Atlantic Canada. The findings indicated that attitudes of adults in the community toward younger youth can limit the volunteer opportunities that are welcoming for this age group, affect younger youths’ perception of their abilities, and influence their enjoyment of the volunteer experience. The important roles facilitators played in younger youths’ access to and enjoyment of volunteer experiences was evident. Youth leaders can help younger youth overcome constraints by ensuring that youth are matched with volunteer tasks that are appropriate for their skill set, are adequately prepared for the tasks and situations that may arise while performing their tasks, participate in tasks with friends, and have chances to discuss their volunteer experiences. Parents can also support involvement through preparing their child for, and debriefing volunteer experiences. Forming partnerships with organizations that need volunteers may be helpful in lessening some of the challenges youth leaders encounter when trying to facilitate volunteering experiences for younger youth. Efforts to educate the public about the abilities of younger youth to contribute to their community may be important in shifting attitudes and increasing the welcoming opportunities available.?
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".