Bibliographic record
Abstract
This edited collection sheds light on how the COVID-19 pandemic has exacerbated pre-existing social issues, and it stresses the importance of understanding, analyzing, and critiquing law and policy decisions during times of crisis. Specifically, this collection brings together a diverse array of scholarly work that highlights various legal and policy-related topics, including litigations, Zoombombing, international students’ experiences, violence against women, sex workers’ health, governmental crisis responses, neo-vagrancy laws, period povery, and educational issues. The collection offers multi-disciplinary scholarly insights, preliminary research findings, legal and policy analysis, and educational guidelines to address unprecedented socio-legal and psychological impacts on society that have evolved since the onset of the pandemic. Further, these chapters add to the ongoing dialogue about how North American society can improve by exploring dilemmas and highlighting opportunities for positive change. Thus, this collection sheds light on how vulnerable communities have been disproportionately impacted by governments’ policies and laws since the onset of the COVID-19 pandemic, and it aims to give a different perspective on how we can move forward and address these issues to create more justice in a post-COVID society. "This publication provides a diverse array of topics, and offers thoughtful and innovative perspectives on the impacts of COVID-19 and policy responses of governments to this pandemic in areas such as litigation, Zoombombing, international students, domestic violence, sex workers’ health, neo-vagrancy laws, and education. The overwhelming and well documented conclusion is that disadvantaged and vulnerable people were disproportionately affected in ways that exacerbated underlying inequalities. It is a timely and vital read for anyone who is concerned about social justice issues." —Dr. A. Wayne MacKay, C.M., K.C., Professor Emeritus of Law, Schulich School of Law, Dalhousie University
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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".