Bibliographic record
Abstract
Disability arises from the dynamic between people’s physical and mental conditions and the physical and attitudinal barriers in the environment. Applying this idea about disability to United States and Canadian immigration law draws attention to barriers to entry and eventual citizenship for individuals who have disabilities. Historically, North American law excluded many classes of immigrants, including those with intellectual disabilities, mental illness, physical defects, and conditions likely to cause dependency. Though exclusions for individuals likely to draw excessive public resources and those with communicable diseases still exist in Canada and the United States, in recent years the United States permitted legalization for severely disabled undocumented immigrants already in the country, and both countries abolished most exclusions from entry for immigrants with specific disabling conditions. Liberalization also occurred with regard to U.S. naturalization requirements. Challenges continue, however. Under U.S. law, vast discretion remains with regard to the likely-public-charge exclusion, because consular officers abroad decide unilaterally whether to issue immigrant visas. Moreover, conduct related to mental disability, including petty criminality, can result in removal from the United States, and individuals with mental disabilities have only modest safeguards in removal proceedings. In Canada, families who have children with disabilities find themselves excluded from legal status because of supposed excessive demands on public resources, although an individual’s disability may provide grounds for avoiding removal in certain cases. The relaxation of some immigration exclusions in Canada and the U.S. and of some U.S. requirements for citizenship illustrates a significant, though conspicuously incomplete, removal of disability-related barriers in North American law and society.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".