Building social capital after Hurricane Katrina
Bibliographic record
Abstract
Disaster response is a vital field in social work practice. Social workers commonly treat posttraumatic stress, assist in planning, logistics, and the protection of vulnerable populations. In 'complex disasters', where official sources of assistance have limited reach, social workers are called upon to adopt an increased coordination and networking role within the community. The case of Hurricane Katrina in 2005 is frequently studied because its protracted recovery illuminated the importance of community networks. However, although the social work literature analyzes efforts towards community development by local residents, there is a gap in the study of the efforts undertaken by social workers themselves. This study investigates the action of social workers in improving social networks during Hurricane Katrina. A case study of the hurricane was conducted using archives from the year 2005 to 2010. Reports of social worker activity in the aftermath of the disaster were analyzed using social capital theory for evidence of attempts to build social networks via bonding (homophilous), bridging (heterophilous) and linking (institutional) exchanges. Social workers were found to have facilitated bonding social capital between themselves and their clients, their own families, and within the social work profession. Bridging social capital was at times increased between geographic, cultural and racial communities, but social workers were not immune to prejudices which could impede this process. Linking social capital was very difficult to provide, as access to institutional sources of assistance could be sporadic and inconsistent. Nevertheless, there was evidence that linking capital was built between vulnerable populations and helping agencies, clinics, the military, as well as faith-based and other community organizations. The presence of the practitioner-client relationship presented distinct opportunities and obstacles and differentiated the social capital exchanges in
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".