Green social work educational resources in Canada
Bibliographic record
Abstract
Green social work (GSW) is a relatively new framework within social work. The primary objective of this approach is to integrate an environmental focus. GSW aims to address economic oppression, engage in disaster resilience, and sustainable practices. The project GSW Education in Canada aims to comprehensively examine the Canadian schools of social work programs (Bachelor, Master, and Ph.D.), related courses, areas of faculty specialization, and placement opportunities. This project examines the level of GSW teaching and knowledge mobilization in the Canadian social work educational system. Consequently, through website keywords (e.g., climate change, disaster, environment, green social work, and sustainability) searching, data from the academic institutions’ official websites for 45 universities and colleges were collected. These data include (1) course descriptions, (2) faculty members areas of research and/or practice, (3) when possible, social work field placement opportunities. The first iteration of this data included information about faculty members, including name and research or practice specialization. However, faculty members’ data is not able to be published due to privacy and ethical concerns. This data set emphasizes the Canadian post-secondary institutions’ emphasis or lack of focus on GSW. This information might encourage schools of social work and faculty members to promote GSW research, teaching, and practice through integrating disaster response, climate change, and sustainability practices. International and Canadian social work researchers could use this data to identify future research collaborations across Canadian geographical areas where GSW curricula can be further developed. Prospective social work students can use this data to find GSW-related programs and courses and network with faculty members with related research interests. For the public, this data can provide information about social work courses and curricula across Canada and highlight the scholars with relevant expertise amongst the institutions.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.020 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.002 |
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".