Role Commitment and Role Maintenance Strategies: A Symbolic interactionist Approach to Volunteering
Bibliographic record
Abstract
There are numerous reports on the rates of attrition among volunteers as a persistent challenge for organizations. In explaining volunteer attrition, researchers have predominantly: 1) provided an individualistic account of volunteering; 2) overlooked the interactional dimension of volunteer work and the crucial role of interpretation in its development; and 3) assumed commitment as a function of satisfaction with volunteering experience. Drawing on the theoretical insights of a symbolic interactionist approach, this article contends that volunteers’ role commitment hinges on their satisfaction with their interpretation of their interaction with clients, rather than the interaction itself. This perspective calls attention to the volunteer-client dyadic interaction, gives a prominent place to the social role and its definition, and draws attention to strategies used by volunteers to sustain challenging relationship with clients. RÉSUMÉIl existe de nombreux rapports sur les pourcentages de bénévoles perdus et le défi que ces pertes posent pour les organismes. Pour expliquer ces bénévoles perdus, les chercheurs ont surtout : 1) fourni des comptes rendus individualistes du bénévolat; 2) ignoré la dimension interactionnelle du bénévolat et le rôle crucial de l’interprétation dans le développement des interactions; et 3) pris pour acquis l’engagement comme indice de satisfaction des bénévoles. Se fondant sur la perspective théorique offerte par l’interactionnisme symbolique, cet article maintient que l’engagement des bénévoles dépend de la manière dont ils interprètent leurs interactions avec les clients plutôt que des interactions elles-mêmes. Cette perspective met l’accent sur l’interaction dyadique entre le bénévole et le client, donne une place de choix au rôle social et à sa définition, et attire l’attention sur les stratégies employées par les bénévoles pour gérer des rapports parfois difficiles avec leurs clients.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".