Altruism at Work: An Integrated Approach to Voluntary Service among Private Practice Lawyers
Bibliographic record
Abstract
Explanations of altruism remain fragmented across disciplinary lines and focus heavily on phenomena such as philanthropy, the nonprofit sector, and volunteering outside the workplace. Yet numerous professions, including law, claim a duty of service that calls on their members to volunteer. Using a mixed methods approach that draws on thirty interviews and a survey of 845 lawyers, the authors develop an integrated framework on altruism to account for how volunteering takes place in the course of law practice. The analysis reveals psychological traits, collective norms, exchange relationships, and organizational dimensions that shape lawyers’ volunteering. In particular, a cultural norm endorsing volunteer efforts is a powerful driver of volunteering legal services. At the same time, organizational features, such as time constraints, condition cultural norms to hinder volunteering, while business opportunities for client recruitment condition cultural norms to foster volunteering. We conclude with directions for advancing our integrated approach to altruism in the context of lawyers’ professional service.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".