Voluntary Labor, Responsible Citizenship, and International NGOs
Bibliographic record
Abstract
This article focuses on the relationship between volunteer labor and responsible citizenship in an international NGO context. Situated within critical assessments of the voluntary sector, the article examines how voluntary labor is increasingly shaped and steered by the initiatives of advanced liberalism. Under advanced liberalism, diverse tasks of government are redirected from state bureaucracy and distributed to various organizations, agencies, individuals, and citizen groups. Within this context, it explores some key social transformations that have led to an increasing reliance on voluntary labor in both government and international NGOs. It emphasizes that a range of authorities establish the contemporary voluntary sector as a site for providing answers and solutions to social and economic problems that are now determined to lie outside the reach of the formal domain of the state. Through the use of substantive international examples on voluntary labor in the international development NGO sector, the authors argue that this sector is increasingly implicated in assembling volunteers as ‘responsible citizens' in the delivery of public services. This responsibilization process produces new effects and plans of actions that are different from the way traditional liberal approaches viewed volunteers and volunteerism. The work calls attention to contemporary concerns underscoring voluntary labor and international NGOs, and raises broader questions pertaining to issues of social justice.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.030 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| 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".