Active Negotiation: Mothers with Intellectual Disabilities Creating Their Social Support Networks
Bibliographic record
Abstract
Background The support networks of mothers with intellectual disabilities play an important role in caring for children. Understanding the support provided by the network is therefore vital in understanding the capacity of a mother to care for her child. Nevertheless, how these important networks came into existence is yet to be explored. Furthermore, the other functions support networks may serve are poorly understood, apart from assistance with child care. Materials and Methods This paper reports some findings from a phenomenological study into becoming a mother for women with intellectual disabilities. Semi‐structured interviews were conducted with 17 expectant mothers with intellectual disabilities. One part of the phenomenon, ‘negotiating a support network for me and my baby’ is described. Results Expectant mothers strategically negotiated support networks prior to the baby’s birth. They sought practical assistance for the tasks of mothering from those who acknowledged them as the most important person in their baby’s life. Conclusions The findings have implications for the practitioners engaged in supporting mothers and their children, particularly those who are a part of the lives of women with intellectual disabilities and their children due to a court order.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".