The Caring Encounters Guiding Framework: A Narrative Inquiry-Informed Innovative Model for Navigating Diversity
Bibliographic record
Abstract
Abstract Countries worldwide are characterised by increasing diversity. In Western societies, social diversification has contributed to escalating tension amongst people holding different worldviews. The emergence of what some have called superdiverse societies has led to calls for new models to assist social workers navigate differences. In response, the present study developed an innovative model—the Caring Encounters Guiding Framework—to successfully navigate difficult interactions. To develop this model, narrative inquiry was used with a sample of thirty-two individuals who self-identified as members of diverse groups. Analysis produced a preliminary Framework comprising three interconnected elements: Context, Core Issues and Prescriptions. The Framework provides guiding principles and processes for transversing interactions in both direct practice and educational settings. Included amongst these are considering the context in which interactions occur, attending to how differences are perceived and discussed, and using flexibility in approaching each interaction. Implementing the strategies embedded in this Framework positions social workers to interact with each individual in a caring and sensitive manner that respects their unique differences and cultural backgrounds.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".