Disciplining the risky subject: a discourse analysis of the concept of resilience in social work literature
Bibliographic record
Abstract
Summary The concept of resilience has become an established, taken-for-granted concept in social work. This poststructuralist discourse analysis of randomly sampled social work articles on resilience examines the discursive mechanisms through which the concept of resilience has been constructed in particular ways and considers the political effects of such usage. Findings The study of resilience is always a post facto analysis; markers of resilience are predetermined by dominant ideas of the normal and the normative subject. Systemic risk factors such as poverty and inequality are acknowledged to be productive of subjects in need of resilience. Yet, those structures are relegated to the margins of the manuscript and elided in favor of individualized analysis and intervention; the identified locus of risk and the targeted site of interventions are entirely at odds. Resilience, thus, serves as a designation for risky subjects’ capacity to accommodate—not actively change—their social/political environments, including their interactions with social work and social workers. It functions as a technology of the neoliberal self that allows social workers to construct and manage subjects capable of self-management and productive self-sufficiency. Application The resilience enterprise thus short-circuits social work’s aims for social justice. Examination of the discourse of resilience for their implications for practice, education, and research is a political imperative for social work and is necessary to open up new sightlines of possibility for a reenergized, more complex social work praxis. Suggestions for future directions are included.
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 | 0.020 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.017 | 0.034 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".