Journal of Sociology and Social Welfare Vol. 46 No. 1
Bibliographic record
Abstract
According to the NASW Code of Ethics, social workers are called to engage in political activity at the micro, mezzo and macro levels for the advancement of social justice and human rights.NASW has mechanisms in place to aggregate the voices of individual social workers through political activity.Drawing on a model of civic voluntarism, the aim of this study was to examine the impact of political activity on decisions by Texas social workers to join or re-join NASW, as well as their opinions on the political engagement of NASW/Texas.This study employs a non-experimental, exploratory, cross-sectional survey design to assess political participation of social workers and their view of how politically active NASW as an organization should be.The survey was sent to all attendees of the 2013 NASW/Texas Conference, held in Austin, Texas.The conference attendees (n = 789) included NASW members (n = 643), and non-members (n = 146).A total of 148 responded to the survey, yielding a 19% response rate.The findings of the study suggest that political activity at the organizational level positively impacts social workers' decisions to join or maintain their NASW membership.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.027 | 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".