Anti-Oppressive Organisational Dynamics in the Social Services: A Literature Review
Bibliographic record
Abstract
Abstract Social service organisations are designed to serve the most vulnerable in our communities, many of whom have experienced oppression in the form of discrimination, marginalisation and violence. Despite their service-oriented mission, social service organisations also contribute to the oppression of service users through negative interactions with staff and inaccessible or discriminatory organisational policies and practices. This study provides a comprehensive literature analysis of empirical and conceptual literature related to organisational practice and anti-oppression. It is based on the theory that organisational factors such as workplace culture and values impact service user experiences. In this literature analysis, 6,459 abstracts were reviewed and 361, which met the inclusion criteria, were included in this study. Themes that emerged included: (i) forms of oppression experienced by service users, (ii) ways that social service organisations can address oppression and (iii) organisational factors that impact service user oppression. The findings highlight key organisational dynamics to consider in developing an anti-oppressive organisational environment, and can support further quantitative research that aims to assess the impact of anti-oppressive organisational processes and dynamics on service user outcomes.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".