Bridging or Deepening the Digital Divide: Influence of Household Internet Access on Formal and Informal Volunteering
Bibliographic record
Abstract
The digital divide persists; a quarter of the U.S. population is unconnected, left without Internet access at home. Yet volunteer recruitment is increasingly moving online to reach a broader audience. Despite widespread use, little is known about whether the lack of digital access has repercussions on connections offline in the community. We examine the influence of access on volunteering across four critical aspects—structure, time devoted, level of professionalization, and pathways to volunteering. We find home Internet access has an independent influence on volunteering even after controlling for socioeconomic status. Those with access are more likely to volunteer, formally and informally, and are more likely to become volunteers because they were asked. However, digitally unconnected volunteers devote more time. Nonprofit organizations and government agencies should be strategic and inclusive in their volunteer recruitment efforts to ensure they recruit qualified and dedicated volunteers rather than rely solely on digital recruitment strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".