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Record W1550187770 · doi:10.18438/b8nk75

Public Libraries Can Play an Important Role in the Aftermath of a Natural Disaster

2010· article· en· W1550187770 on OpenAlexaffvenue
Virginia Wilson

Bibliographic record

VenueEvidence Based Library and Information Practice · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNarrativeLibrary scienceThematic analysisHurricane katrinaPublic relationsNatural disasterSociologyQualitative researchPolitical scienceGeographyComputer scienceSocial science

Abstract

fetched live from OpenAlex

A Review of:
 Welsh, T. S. & Higgins, S. E. (2009). Public libraries post-Hurricane Katrina: A pilot study. Library Review, 58(9), 652-659. 
 
 Objective – This paper analyzes Hurricane Katrina-related narratives to document the challenges faced by public libraries after the disaster and the disaster-relief services these libraries provided. 
 
 Design – A qualitative thematic analysis of narratives obtained by convenience sampling.
 
 Setting – Narratives were collected and analyzed in 2005 and 2006 across the Gulf Coast area of the United States.
 
 Subjects – Seventy-two library and information science students enrolled in the University of Southern Mississippi’s School of Library and Information Science. Many worked in local libraries. 
 
 Methods – In this pilot study, students 
 volunteered to participate in a confidential process that involved telling their stories of their post-Hurricane Katrina experiences. Data was collected in a natural setting (the libraries in which the students worked), and inductive reasoning was used to build themes based on these research questions: What post-disaster problems related to public libraries were noted in the students’ narratives? What post-disaster public library services were noted in the narratives?
 
 NVivo7 qualitative analysis software was used to analyze and code the narratives. Passages related to public libraries were coded by library location and student. These passages were analyzed for themes related to post-disaster challenges and disaster-recovery services pertaining to public libraries.
 Main Results – Ten of the 72 narratives contained passages related to public libraries. The libraries included four in Alabama, one in Louisiana, and five in Mississippi. Results related to the first research question (What post-disaster problems related to public libraries were noted in the students’ narrative?) were physical damage to the building, from light damage to total destruction (reported in 8 or 80% of the students’ narratives), and inundation by refugees, evacuees, and relief workers (reported in 8 or 80% of the narratives). Results pertaining to the second research question (What post-disaster public library services were noted in the narratives?) included providing information for things such as providing information via the use of computers and the filling out of the Federal Emergency Management Agency and Red Cross aid forms (6 or 60% of the narratives included this), listening and providing comfort (5 or 50% of the narratives), and volunteering and donating, both from others and of the students’ own time, money, or materials (noted by 5 or 50% of the narratives).
 
 Conclusion – The researchers concluded that while public libraries suffered devastation during the hurricane, after the hurricane, those libraries that could open provided essential services to people in need. These services included providing access to computers and access to information via computers, aid in filling out necessary relief aid forms, listening and providing comfort, and volunteering time, money, and materials. The public library clearly played a role in both providing information and facilitating communication. Documenting such contributions serves to illustrate the value of public libraries, especially in a post-disaster setting, and helps to demonstrate the value of public libraries in their communities.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.412
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.276
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations2
Published2010
Admission routes2
Has abstractyes

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