Bibliographic record
Abstract
Using an anti-oppressive practice (AOP) theoretical framework and an exploratory qualitative research design, featuring semi-structured interviews and written assignments, a group of ten social workers were asked to describe their understandings of the concept of oppression. The study found that, in the case of these particular social workers, they used metaphor as a key conceptualization process to more vividly describe and understand the concept of oppression within their social work practice. This article analyzes eight categories of metaphor themes the participants used to explain their understanding of oppression: (a) pressure; (b) earth; (c) quest; (d) nature of society; (e) seeing; (f) building; (g) dancing; and (h) water. The research findings are intended to open up dialogue and thinking about the concept of oppression, increase our knowledge base and understandings of oppression within social work practice, and assist the social work profession to build a stronger conceptual framework for understanding and naming oppression with the end goal of assisting social workers to better respond to and resist systems of domination.
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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.009 | 0.043 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".