Bibliographic record
Abstract
Given our commitment to highlighting current issues, challenges, and responses within social work practice and education globally, the Spring 2021 issue of Advances in Social Work is pleased to present 11 full-length papers written by 40 authors from across the U.S. and Canada. We begin with four papers calling for greater involvement of social work educators and practitioners in arenas including information literacy, dyslexia, digital equity, and independent living. These papers are followed by reports on seven empirical studies in areas of practice as diverse as kinship care, legal representation, collaboration in a dental clinic, and dance and mindfulness. We hope you find these selections on emerging areas of social work practice and education to be informative and inspiring. Each contribution to this issue is introduced below. Sprecial Issue Alert: Just a heads up that our next special issue, Dismantling White Supremacy in Social Work Education, will be released in late summer 2021. With over 100 abstracts submitted, this special issue has garnered incredible interest. We are looking forward to bringing you 34+ original papers (our largest issue to date!) addressing ways that social work education can move forward positively and intentionally in ways that acknowledge the damage wrought by white privilege, promote racial justice and anti-racist practice, and embrace new ways of knowing, teaching, and learning. The Indiana University School of Social Work, through publishing Advances in Social Work as an open access scholarly journal, is grateful to play a role in knowledge production and dissemination in social work. We are continually amazed at the dedication and hard work of our social work colleagues globally who work tirelessly to advance social and economic justice. Marshall on, colleagues! Tribute to Retiring Board Members: Before closing, I would like to take this opportunity to express sincere appreciation to three outgoing AISW Board members who recently retired from the Indiana University School of Social Work: Dr. Karen Allen, Dr. Larry Bennett, and Dr. Bob Vernon. Your contributions to not only Advances in Social Work but to the IU School of Social Work and to the social work profession at large are very much appreciated. Special accolades to Dr. Vernon who has served on the AISW Editorial Board since its inception in 1999. Best wishes to each of you in your next adventures!
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.285 | 0.206 |
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".