Head Starts and Extra Time: Academic Accommodation on Post-Secondary Exams and Assignments for Cognitive and Mental Disabilities
Bibliographic record
Abstract
Universities and colleges routinely grant extra time on exams and assignments to accommodate students with cognitive and mental disabilities. Such accommodation is inappropriate and inconsistent with the law. Exams and assignments are, in part, competitions. Like a head start in a race, extra time means that the competition is no longer valid. Races test speed, and no accommodation can be made for disabilities that affect speed, which is the bona fide criterion of the race. Exams and assignments assess a range of cognitive and mental skills, and no accommodation can be made for disabilities that affect those skills, which are bona fide criteria of the assessment. A head start imposes undue hardship on other runners, and extra time imposes undue hardship on other students in the class. The purpose of accommodation is to facilitate participation, not to compensate for lack of ability that is relevant to the test. Students with mental disabilities are able to sit exams without extra time, which means that they are already able to participate. The real purpose of claims for extra time is to increase their prospects for success at the expense of other students, which is not legitimate. Universities and colleges should not provide extra time as an accommodation for disabilities that relate to cognitive and mental skills.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.078 | 0.017 |
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".