How First Nations peoples living in the Torres Strait and Northern Peninsula Area describe and discuss social and emotional well‐being
Bibliographic record
Abstract
OBJECTIVE: This study was the first phase of a broader project designed to develop a new tool to screen social and emotional well-being (SEWB). Its objective was to identify words used by First Nations people living in the Torres Strait (Zenadth Kes) and Northern Peninsula Area (NPA) to describe and discuss SEWB. We pay our respects to Elders past and present. We acknowledge the First Nations peoples who took part in this project as holders of their cultural knowledge now and forevermore. SETTING: This study took place in community and primary health care settings located on islands of the Torres Strait and NPA of Australia. PARTICIPANTS: Twelve yarns with 35 community members and health professionals were led by Torres Strait Islander members of the project team between August and December 2022. DESIGN: This study employed a descriptive qualitative design. Yarning, an Australian First Nations relational method, was used to share stories about SEWB. All but one yarn was audio recorded and subsequently professionally transcribed. Inductive thematic analysis was used to analyse the yarns. RESULTS: Worry, sad and stress were the words most often used by participants to describe feelings of low SEWB. Signs of low SEWB included behaviour change, particularly significantly reduced community engagement. CONCLUSIONS: Worry is not a word that is used in Australian mainstream tools that screen for psychological distress. Findings of this study indicate that a question that asks about worries should be included when screening for low SEWB in Australian First Nations peoples living in the Torres Strait and NPA.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".