From Antagonism to Care: Reimagining Academic Freedom and Justice in Higher Education (Guest Editors' Introduction)
Bibliographic record
Abstract
The papers included in this special issue of Studies in Social Justice originally stem from the draft papers presented at this conference.In our call for papers, we understood the need to recognize how antagonism in the academy works on the ground.In other words, how it can target welltrained faculty members and students and erode their research work or related activities; how it can undermine academic freedom, that is, from a human rights standpoint, "the human right to acquire, develop, transmit, apply, and engage with a diversity of knowledge and ideas through research, teaching, learning, and discourse" (Scholars at Risk [SAR], 2024, p. 8).Additionally, how it can connect to political or religious interference in research and teaching and articulate issues of social injustice and social justice.This special issue comprises papers that discuss various aspects of antagonism and intimidation in academia, including the role of censorship, unimpeded corporate interests, gender and sexuality relations, race and ethnicity matters, exclusionary politics and power dynamics, and institutional practices and relations in higher education.It also offers strategies for creating constructive and germane dialogue and effective tools for community and social justice engagement, and for enhancing safe environments for critical thinking, openness, and solidaritybuilding.Several contributions discuss approaches that involve engagement in meaningful debate with opposing, and even highly controversial, standpoints.Alongside these key concerns, some papers emphasize the concept of trust, which is explored for its significance in higher education institutions and related societal contexts.Overall, the collection of papers highlights the need to develop or enhance socially just practices and frameworks that can generate spaces of care and inclusion, foster academic freedom as a kind of social responsibility to promote democratic values (see Darian-Smith, 2025), and rebuild trust -both within the academy and with various communities. Academic Work under AttackUniversity scholars across many disciplines increasingly face antagonistic or hostility-based reactions toward their work, particularly those engaged in social justice scholarship primarily in humanities, social sciences, law and legal studies, as well as in other fields such as medicine and sciences.Such scholarship addresses, for example, discrimination based on gender, sexuality, race, ethnicity, and religion.It also speaks to research on vulnerable and precarious individuals and groups; on science, evolution, and technology; on health and medicine issues; and on environment and climate change matters (e.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".