Slouching Toward Regulation: Assessing Bill 88 as a Solution for Workplace Surveillance Harms
Bibliographic record
Abstract
Employee monitoring applications (‘‘EMAs”) are proliferating in Canada and provide employers with sophisticated surveillance tools for the monitoring of workers (e.g., on-device video surveillance, browser activity, and email monitoring). In response to concerns about these increasingly invasive surveillance practices, the Government of Ontario passed Bill 88, the Working for Workers Act, 2022, which requires all employers with 25 or more workers to have a written policy stating whether and how they electronically monitor their employees. Bill 88 marks a more explict attempt to regulate workplace surveillance in a modern digital context in Canada; however; however, an analysis of the Bill’s capacity as a meaningful regulatory mechanism has yet to be conducted.\nThis article engages in a critical analysis of Bill 88’s capacity to meaningfully protect employee privacy in a contemporary remote workplace, with particular emphasis on the emergence and use of EMAs. Specifically, we examine the multitude of harms generated by EMAs, situate Bill 88 within existing legislation and common law, identify remaining regulatory gaps within the Bill’s framework, and evaluate its capacity to mitigate surveillance harms. Despite Bill 88’s attempt to better inform Ontario workers about the electronic monitoring practices of their employers, in its current form, we argue that the bill is an incomplete and ineffective comprehensive regulatory solution for EMAs. The primary objective of Bill 88, to enhance transparency, and the Bill’s framing of workplace surveillance harms through the lens of ‘‘individual privacy,” limit more meaningful regulatory interventions that might otherwise address the harm-generating mechanisms of EMAs themselves.\nWe recommend that Bill 88 be meaningfully amended to (a) consider the numerous impacts of workplace surveillance that extend beyond a narrow privacy framework (e.g., social, psychological), (b) place restrictions on employers on when, where, and how EMAs can be used, and (c) afford workers with the right to file complaints related to the necessity and proportionality of EMA use employers.\n--\nLes applications de surveillance des employe´s (« EMA ») prolife`rent au Canada et fournissent aux employeurs des outils de surveillance sophistique´s pour la surveillance des travailleurs (par exemple, la surveillance vide´o sur l’appareil, l’activite´ du navigateur et la surveillance des courriels). En re´ponse aux pre´occupations concernant ces pratiques de surveillance de plus en plus envahissantes, le gouvernement de l’Ontario a adopte´ le projet de loi 88, la Loi de 2022 sur le travail pour les travailleurs, qui oblige tous les employeurs de 25 travailleurs ou plus a` avoir une politique e´crite indiquant s’ils surveillent e´lectroniquement leurs employe´s et comment ils le font. Le projet de loi 88 marque une tentative plus explicite de re´glementer la surveillance en milieu travail dans un contexte nume´rique moderne au Canada; cependant, une analyse de la capacite´ du projet de loi en tant que me´canisme de re´glementation significatif n’a pas encore e´te´ mene´e.\nCet article s’engage dans une analyse critique de la capacite´ du projet de loi 88 a` prote´ger de manie`re significative la vie prive´e des employe´s dans un lieu de travail contemporain a` distance, avec un accent particulier sur l’e´mergence et l’utilisation des EMA. Plus pre´cise´ment, nous examinons la multitude de me´faits ge´ne´re´s par les EMA, situons le projet de loi 88 dans la le´gislation existante et la common law, identifions les lacunes re´glementaires restantes dans le cadre du projet de loi et e´valuons sa capacite´ a` atte´nuer les me´faits de la surveillance. Malgre´ la tentative du projet de loi 88 de mieux informer les travailleurs ontariens sur les pratiques de surveillance e´lectronique de leurs employeurs, dans sa forme actuelle, nous soutenons que le projet de loi est une solution re´glementaire comple`te incomple`te et inefficace pour les EMA. L’objectif principal du projet de loi 88, a` savoir ame´liorer la transparence, et le cadre du projet de loi sur les me´faits de la surveillance du lieu de travail a` travers le prisme de la «vie prive´e individuelle», limitent les interventions re´glementaires plus significatives qui pourraient autrement s’attaquer aux me´canismes ge´ne´rateurs de pre´judices des EMA elles-meˆmes\nNous recommandons que le projet de loi 88 soit modifie´ de manie`re significative pour (a) tenir compte des nombreux impacts de la surveillance du lieu de travail qui vont au-dela` d’un cadre e´troit de confidentialite´ (par exemple, social, psychologique, etc.), (b) imposer des restrictions aux employeurs sur le moment, le lieu et comment les EMA peuvent eˆtre utilise´es, et (c) donner aux travailleurs le droit de de´poser des plaintes lie´es a` la ne´cessite´ et a` la proportionnalite´ de l’utilisation de l’EMA par les employeurs.
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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 | 0.127 | 0.220 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.016 | 0.039 |
| Scholarly communication | 0.026 | 0.018 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 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".