Bibliographic record
Abstract
The world's first "molecular disease," sickle cell disease (SCD) has captivated the medical community's attention as a multisystem blood disorder linked to abnormalities in one molecule: hemoglobin. While the molecular model of SCD has led to advances in medical management, its reductionism obfuscates the sociopolitical dimensions of the condition, affording little attention to the racialized, gendered, classed, and disabling disparities faced by people with SCD. Consequently, SCD is frequently contested as a disability-opportunities to support people with SCD in everyday challenges escape many healthcare providers. These trends speak to the legacy of anti-Black racism in the Global North, which deeply entwines disability with racialized boundaries of citizenship and broader debates about "deservingness" of welfare. To address these gaps, this article delineates the medical and social models of disability as well as anti-Black racism to explore how social workers can embed human rights for people with SCD in everyday practice. This article is contextualized in Ontario, Canada, a province that recently launched a quality standard, Sickle Cell Disease: Care for People of All Ages.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".