Hearing from First Nations Dads: Qualitative yarns informing service planning and practice in urban Australia
Bibliographic record
Abstract
Abstract Objective This qualitative study explores the experiences and perceptions of new and expectant First Nations fathers in an urban setting in Australia. Background Little is known about the experiences of First Nations men as fathers, including their transition to fatherhood and their strengths and challenges as fathers. Method Eight First Nations men who were expectant or new fathers participated in individual yarning interviews. Data were analyzed using descriptive phenomenological analysis. Results Men perceived a father to be a protector, provider and someone who reflects on how to be a better father. To be a better father, men were trying to heal and learn from their past and build their identity as a father, while managing the stress of fatherhood. Conclusion The study identified four strategies to support new First Nations fathers: (a) create gathering places for men to connect with and learn from other dads, (b) maternity and early childhood services should be inclusive of men and their role as fathers, (c) clinical intervention and supportive pathways into fatherhood, and (d) promote and celebrate the strengths and roles of First Nations fathers. Implications Maternity and early childhood services can better support First Nations men in their transition to fatherhood by being more responsive to their needs and inclusive of their important role in child development and strengthening the family unit.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".