Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Does volunteering causally improve well-being? To empirically test this question, we examined one instantiation of volunteering that is common at post-secondary institutions across North America: community service learning (CSL). CSL is a form of experiential learning that combines volunteer work with intentional learning goals and active reflection. We partnered with an academic program that randomly assigns interested students to participate in a CSL program or to a wait-list. As part of this CSL program, students are required to engage in 10–12 h of formal volunteering each week in addition to completing related coursework. To assess the well-being benefits of formal volunteering through CSL participation, we examined the subjective well-being (SWB) of students from both groups over a six-month period. Using Bayesian statistics, and comparing a null model to a model specifying a small to moderate benefit of CSL participation, we found conclusive evidence in support of the null model. These findings diverge from previous correlational research in this area by providing no evidence for the causal benefits of volunteering on SWB. These findings highlight the critical importance of using experimental methodology to establish the causal benefits of volunteer work, such as the experiences provided by CSL programs, on SWB.
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.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 it