Autism Spectrum Disorder and Maternal Employment Barriers: A Comprehensive Gender-Based Inquiry
Bibliographic record
Abstract
This paper presents a systematic literature review of the autism spectrum disorder (ASD) and maternal employment disruption in order to explore what mothers of these children do using a critical lens. Although a broad range of peer-reviewed scholarly publications exist on many topics related to ASD, specific family issues such as the potential employment challenges of the maternal employment of children with ASD, have been explored in less detail until recently. ASD has generated much discussion and research. We report the most recent data over the last decade.Through a comprehensive literature review, we identify a range of papers on the topic of ASD and parental employment disruption. This project, then, highlights relevant international Canadian and internationals research findings, including the United States, China, the United Kingdom (UK) and Sweden. The review and its critical commentary show how structures which act to exclude children with ASD cause parents to seek employment adjustments in order to manage their complex situations. Parents, especially mothers of children with ASD, have fewer employment opportunities. This situation has substantial economic impact on families. This trend extends beyond preschool child care as obtaining capable and reliable child care support is an ongoing issue that exists well into the school years—and beyond. Supportive, accommodating, and especially flexible employment situations make employment possible, at times, for mothers of children with ASD.
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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 | 0.014 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".