Bibliographic record
Abstract
• Summary: In a recent issue of this journal, Marlee Spafford and her colleagues reported on a Canadian study of social work, medical and optometry students. One of their findings was that the novice social workers viewed the acknowledgement of uncertainty as a hallmark of professional competence. Drawing on data from UK-based studies of professional reasoning, this article challenges the notion that social work has embraced and engaged with uncertainty. • Findings: Despite the obvious ambiguities of many cases, much of the time social workers often feel very sure of their formulations. This is because social work takes place in the terrain of human relationships about which we all, qua human beings, routinely make moral evaluations in everyday life. Rhetoric of complexity and reflection should not be confused with uncertainty. • Applications : This article endorses Spafford et al.'s respect for uncertainty and tentativeness, but argues that it is folly to think that we already have it in social work. A tentative and sceptical vocabulary of the emotional and moral domain is required if social work is indeed to embrace and acknowledge the limits and fallibilities of its technologies and practices.
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 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 | 0.024 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.044 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".