‘My mom was my left arm’: The lived experience of ableism for girls with Spina Bifida
Bibliographic record
Abstract
In many cultures, people deemed different, deficient or of lesser value are socially marginalized, disempowered, devalued and face innumerable barriers to health and quality of life. Persons deemed disabled are one such group. Through oppression, discrimination, and constant degradation, marginalized groups are denied the basic human right of dignity. For five girls with Spina Bifida, the experience of societal ableism, i.e. the belief that being able bodied is normal, eroded their sense of self worth, impinged upon their human rights, and isolated them in their own degradation - until they came together and spoke. My Mom Was My Left Arm illuminates the impact of ableism on the health and well-being of girls living with Spina Bifida. Several focus groups with five girls concerning their lives, anger and health yielded compelling reasons for today's contemporary nurse to explicitly practice from a social justice framework. In being deemed other, less than and viewed as their disability, the young women interviewed believed they had never reached their actual life potential. The relationship between health and ableist discrimination as lived by young women with Spina Bifida will be explored. The paper will close with nursing's ethical imperative to advocate for social justice, equity, fairness and dignity.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".