Bibliographic record
Abstract
I use a volunteer process model to organize a review of recent research on volunteerism, focusing mainly on journal articles reporting survey research results. Scholars from several different disciplines and countries have contributed to a body of work that is becoming more theoretically sophisticated and methodologically rigorous. The first stage of the process model—antecedents of volunteering—continues to attract the most attention but more and more scholars are paying attention to the third stage, the consequences of volunteering, particularly with respect to health benefits. The middle stage—the experience of volunteering—remains somewhat neglected, particularly the influence of the social context of volunteer work on the volunteer’s satisfaction and commitment. Keywords volunteers, motivations, resources, experiences, consequences In the last quarter of a century the study of volunteer work has assumed its rightful place at the core of the social sciences, no longer relegated to the status of a peripheral and inconsequential leisure pursuit or dismissed as an oddity in a world largely given over to the pursuit of self-interest. Since the publication of Smith’s (1975) initial assessment of the study of “voluntary participation, ” theories have become more sophis-ticated, methods more refined, and data more abundant. Articles on volunteering are to be found in an ever-expanding range of scholarly journals. In this review article I describe the research on volunteerism published since 2008 when Marc Musick and I concluded our work on Volunteers: A Social Profile, with the addition of a few studies we overlooked at the time. I do not attempt to give thorough descriptions of every study but focus instead on what I believe to be the most interesting at PENNSYLVANIA STATE UNIV on May 10, 2016nvs.sagepub.comDownloaded from
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.051 | 0.029 |
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".