Theory and practice of integrative clinical ethics support: a joint experience within gender affirmative care
Bibliographic record
Abstract
BACKGROUND: Clinical ethics support (CES) aims to support health care professionals in dealing with ethical issues in clinical practice. Although the prevalence of CES is increasing, it does meet challenges and pressing questions regarding implementation and organization. In this paper we present a specific way of organizing CES, which we have called integrative CES, and argue that this approach meets some of the challenges regarding implementation and organization. METHODS: This integrative approach was developed in an iterative process, combining actual experiences in a case study in which we offered CES to a team that provides transgender health care and reflecting on the theoretical underpinnings of our work stemming from pragmatism, hermeneutics and organizational and educational sciences. RESULTS: In this paper we describe five key characteristics of an integrative approach to CES; 1. Positioning CES more within care practices, 2. Involving new perspectives, 3. Creating co-ownership of CES, 4. Paying attention to follow up, and 5. Developing innovative CES activities through an emerging design. CONCLUSIONS: In the discussion we compare this approach to the integrated approach to CES developed in the US and the hub and spokes strategy developed in Canada. Furthermore, we reflect on how an integrative approach to CES can help to handle some of the challenges of current CES.
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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 | 0.116 | 0.952 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.062 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".