Social Work and Technology: Using Geographic Information Systems to Leverage Community Development Responses to Hate Crimes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study highlights technology use in community development showing how social workers, police, and neighborhood residents promote safer neighborhoods. The approach used was geographic information systems (GIS) to target specific neighborhoods characterized as needing timely interventions. GIS is a technological sub-specialty and form of spatial cartography allowing data to be stored, manipulated, and visually displayed. This article focuses on how social workers can apply such approaches to enhance their communities and neighborhood residents. We offer a case study of a hate crimes project in Canada that brought together university researchers and a local police service into a research project, designed to identify specific neighborhood places where hate crimes were occurring. We propose that community social workers can form meaningful partnerships with technology experts and leverage this relationship into an expanded practice skill with tangible improvements to the communities they work with.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it