Handicapped Workers: Who Should Bear the Burden of Proving Job Qualifications?
Bibliographic record
Abstract
Joining a growing number of jurisdictions in 1973, the Maine Legislature amended the fair employment sections of the Maine Human Rights Act (the MHRA) to extend equal employment opportunity protection to all physically disabled workers. Nearly a decade later the Maine Supreme Judicial Court, sitting as the Law Court, defined unlawful employer treatment of handicapped workers in Maine Human Rights Commission v. Canadian Pacific, Ltd. The Law Court held that an employment decision based on a worker's handicap constitutes an admission of discrimination that shifts the burden of persuasion to the employer to prove either that all workers with similar handicaps are unqualified or that the individual worker in question is not qualified because of reasonably probable health or safety risks. The Law Court reaffirmed its Canadian Pacific holding in Higgins v. Maine Central Railroad. Highlighting the two separate elements of proof allocated to an employer, Higgins held that an employer cannot prove a probable health or safety risk absent an individualized assessment of the worker's handicap at the time the employment decision is made. Although Maine's employers may feel that both cases place an unusually high burden of justification on their employment decisions, the cases are consistent with traditional equal employment opportunity law. Nevertheless, the cases did not present the Law Court with an adequate opportunity to develop an analytic model which fully addresses the distinguishing characteristics of handicap equal employment opportunity law.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.019 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".