Walking with the spectrum: A phenomenological study on the experiences of mothers raising an Autistic child
Bibliographic record
Abstract
The purpose of this study was to explore the experiences of the mothers raising an autistic child, the struggles they faced, the misconceptions they had, the factors that altered their mental framework in effectively managing their child and their condition. 7 Detailed semi structured interviews of mothers raising a child with autism, were conducted to develop a better understanding of their situation and the factors that affected them. A phenomenological methodology was used to uncover the lived experiences of these mothers. Results revealed the existence of 7 distinct themes that provided insight into the real experience of a mother raising a child with autism. Themes focused on the mothers mental frameworks, which included denial of red flags, mother-researcher, emotional paradox, cognitive processing, indicating the thought patterns and emotional processes the mother used in dealing with her child. Moreover themes such as Family dynamics, Societal micro-aggression, medical resistance, the unspoken bond and redefining inclusion were noted for a comprehensive understanding of the experience of raising a child with Autism. The results revealed that although it seems like it is a topic well known, mothers still lack the awareness to detect signs of autism and to manage them effectively, health professionals and families need to work in collaboration to uplift the mother and child from chronic periods of distress.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".