Disabled People and the Intersectional Nature of Social Inclusion
Bibliographic record
Abstract
This editorial introduces a thematic issue of Social Inclusion focusing on disabled people and the intersectional nature of social inclusion. This thematic issue includes transnational and transdisciplinary studies and expressions of lived experiences facing disabled people, their families, and allies across the globe from a social, human rights, and/or disability justice perspective. The articles comprising this issue include an explicit recognition and discussion of intertwined and socially constructed identities, labels, power, and privilege as explicated by pioneering Black feminists who introduced the concept of intersectionality. Taken together, the articles within this issue identify and articulate the powerful ideological forces and subsequent policies and practices working against transformational action. As such, we are not calling for the inclusion of disabled people into society as it is today—wrought with social, economic, and environmental crises. Rather, we seek a transformation of the status quo whereby disabled people are respected as an inherent part of human diversity with gifts and worthiness untangled from a capitalist and colonial system of exploitation, extraction, and oppression. This means that achieving social justice and inclusion requires radically reordering our economic and political systems. This thematic issue illuminates the impacts and root causes of exclusion to foment critical thinking about the possibilities for social inclusion from the perspective of those who are marginalized by the status quo.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| 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".