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Record W7036534687

Building social capital after Hurricane Katrina

2010· dissertation· en· W7036534687 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2010
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsSocial capitalSocial workSocial changeSocial positionBridging (networking)Social engagementCollective actionHurricane katrinaDisaster research
DOInot available

Abstract

fetched live from OpenAlex

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

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.232
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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