In Conversation with a Case Story: Perspectives on Professionalism, Identity and Ethics in Social Work
Bibliographic record
Abstract
In this co-authored article, one contributor presents a case story from an interview with a social worker in Slovenia, while five others offer commentaries on ethical aspects of the case. The story comes from a practitioner working with a pregnant young woman, arranging for adoption following birth. The social worker respected the woman’s request to keep her identity secret, hence not registering her in the institutional records. However, whilst the social worker was on holiday, the baby was born and anonymity was not maintained. Commentaries 1 and 2 evaluate the story through its form: as a narrative with a tempo and plot; and as a performance that creates its narrator as an agent with an ethical identity. Commentary 3 uses a normative moral philosophical framework (virtue ethics), while the final two commentaries take a more grounded approach. Commentary 4 views the social worker as using discretion to act in a space void of rules (there is no provision for anonymous birth), whereas Commentary 5 foregrounds the Slovenian code of ethics as a source of ethical standards unremarked upon by the social worker. The article ends with reflections on the value of exploring multiple perspectives and engaging in dialogue in developing ethical understandings and actions.
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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 | 0.023 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.043 | 0.052 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.015 | 0.021 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".