INVISIBLE STRUGGLES: EXPLORING CHALLENGES FACED BY WOMEN WITH AMPUTATION IN INDIA
Bibliographic record
Abstract
Women in India, particularly those with amputation, face significant challenges, including but not limited to, unequal prosthetic access and satisfaction, societal discrimination, and the physical and emotional consequences of amputation. These challenges are further exacerbated by gender biases towards access to education and socioeconomic factors, which increases their vulnerability to unemployment and mental health issues. This article emphasizes the urgent need for affordable and customizable prosthetic options tailored to the unique needs of women with amputation, particularly those from low-income backgrounds who often face neglect. Thus, addressing these disparities would significantly enhance their overall well-being and independence. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/44002/33160 How To Cite: Alam J, Joshi A, Mir N, Chawla N, Sagar S. Invisible struggles: Exploring challenges faced by women with amputation in India. Canadian Prosthetics & Orthotics Journal. 2024; Volume 7, Issue 1, No.5. https://doi.org/10.33137/cpoj.v7i1.44002 Corresponding Author: Professor Sushma Sagar,Division of Trauma Surgery and Critical Care, Jai Prakash Narayan Apex Trauma Centre, AIIMS, New Delhi, India.E-Mails: sagar.sushma@gmail.com; dr.sushma@aiims.gov.inORCID ID: https://orcid.org/0000-0002-4700-9868
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".