Bibliographic record
Abstract
Research on service-learning and community engagement has exploded over the past decade. It is a field now characterized by increasing methodological and theoretical sophistication, vast quantitative and qualitative studies, interdisciplinary research, myriad subjects, and the internationalization of scholarship.The papers in this volume were selected from nearly 100 presentations made at the 2009 annual conference of the International Association for Research on Service Learning and Community Engagement held in Ottawa, Canada’s national capital. The conference theme, Research for What? emphasized fundamental questions, namely: to what extent is rigorous research uncovering best practices in, and demonstrating the positive results of, service-learning on teaching, learning and building better communities? The papers examine such themes through lenses that include the application of theory to practice, K-12 and university-based service-learning, interdisciplinary initiatives, and international service-learning. The introduction provides an overview of the very recent, but remarkable, growth of service-learning in Canada, and the conclusion, written by the recipient of the Association’s annual Distinguished Researcher Award, discusses major developments, and continuing challenges, in service-learning research.
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.
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 | 0.007 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".