Bibliographic record
Abstract
In 2015, in an unexpected political upset, Alberta’s New Democratic Party was elected to govern for the first time in the province’s history. There were eight social workers amongst those elected, all of whom were interviewed for this research. The purpose of this qualitative study was to explore the motivations that led these social workers to seek political office, to identify factors in their personal and professional histories that explained their high level of political engagement, and to explore how the profession can increase the numbers of social workers pursuing political practice in the future. A standard qualitative thematic analysis of these interviews revealed that families of origin were influential motivators, and that social work education also played a significant role, as did professional experience and networks. Recommendations for change emerged from our findings. We discuss these with an emphasis on professional education and on what the academy can do to heighten levels of political engagement among future graduates.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 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 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".