Mirroring Society? Tracing the Logic of Diversity in the Canadian Journal of Higher Education
Bibliographic record
Abstract
Diversity and equity have become central themes of institutional planning in Canadian post-secondary institutions. The complexity and variance of such activities, and their disconnect from individual experiences, are inherently related to the social norms established by the dominant cultural group. This article argues that published research articles play an important role in reflecting how organizational norms are understood and institutionalized. To trace the normative shifts in how diversity has been addressed in research articles, a systematic analysis of over 186 peer-reviewed articles published in the Canadian Journal of Higher Education between 1971 and 2020 was performed. The findings demonstrate that the concept of diversity has evolved from being examined in narrow binary categories of socio-economic, language, and gender diversity to a more recent focus on intersectionality. The shift from diversity being an issue of individual concern to diversity being a core institu-tional responsibility closely related to student learning is apparent. The article ends with recommendations for future areas of research with specific calls made to increased uptake of critical approaches to diversity for more nuanced perspectives of our accepted social norms in Canadian higher education.
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 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 | 0.027 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.024 | 0.030 |
| Science and technology studies | 0.019 | 0.043 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".