Towards a “New Mothering” Practice? The Life Experiences of Mothers Raising a Child with Autism in Urban Ethiopia
Bibliographic record
Abstract
Autism spectrum disorder (ASD) is a complex neurological and developmental disorder that has seen an increase in prevalence over the past two decades, particularly in low and middle-income countries. The purpose of the current paper is to examine the experiences of mothers in Ethiopia raising a child with ASD through employing a qualitative research design involving semi-structured interviews with twenty mothers. The experiences of mothers in this study fell into three thematic areas: (1) grieving and experiencing other emotions arising from the diagnosis of their child; (2) developing, understanding and defining autism; and (3) accepting the diagnosis and developing coping strategies for raising their child. The findings revealed that raising a child with autism introduced a new lifelong experience to mothers' everyday lives, profoundly changing their parenting role and transforming their view of mothering. Recognition of the experience of "new mothering" and mothers' meaning-making process, stress, coping mechanisms and resilience is critical to informing policies, programs, counseling and other therapeutic efforts to assist children with autism and their families for social workers in Ethiopia and those working with the Ethiopian diaspora in other regions of the world.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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; 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".