Employee Drug Testing: Orwellian Vision or Pragmatic Approach to Problems in the Workforce
Bibliographic record
Abstract
Until very recently, there has been no case law considering the legitimacy of employee drug testing under Human Rights legislation or the permissibility of drug testing policies and what they should stipulate. In light of two relatively recent cases, Entrop v. Imperial Oil and Toronto-Dominion Bank v. Canadian Human Rights Commission and Canadian Civil Liberties Association, a re-examination of the legitimacy of employee drug testing is warranted, along with the arguments concerning what the policies should target and how they should be implemented. Furthermore, the EDT jurisprudence exemplifies the discrepancies in the human rights framework, as articulated by the Supreme Court in British Columbia Government [Public Service Employee Relations Commission] v. BCGSEU. The Ontario Court of Appeal heard Entrop prior to the release of the recent Supreme Court pronouncements on a revised human rights analytical framework, thus providing a further impetus to examine how EDT can justifiably be implemented according to traditional human rights principles embraced in the new "unified approach." Courts should consider employee drug testing to be a practicable and legitimate employment rule that strives to maintain workplace safety and integrity. This conclusion is reached after examining the viable concerns over substance abuse, the various issues that are raised by employee drug testing, the role of human rights and Charter jurisprudence, and the preciseness of the polices' language. The present pending appeal before the Ontario Court of Appeal in Entrop presents a unique opportunity for the judiciary to set out guidelines as to the permissible means of drug testing, the responsibilities of employers and employees, and how testing can be legally upheld under statutory and common law. Employee drug testing is unquestionably an invasion of employees' privacy. But it is also a proactive approach to a pressing issue that confronts the workplace and society at large. Employee assistance programs are a valuable component in an employer's strategy to maintaining a healthy workforce and a safe work environment. But these programs alone are simply not sufficient to combat the danger of substance abuse in the workplace. Unions and management must work together to implement testing policies that meet the changing virtues and vices of contemporary Canadian society in order to accommodate employees' needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".