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Record W4309862086 · doi:10.3389/fsoc.2022.957127

“Go with the Flo”: Conducting rapid research on prenatal stress following Hurricane Florence as participant observers

2022· article· en· W4309862086 on OpenAlexaff
Michaela Howells, Kelsey N. Dancause

Bibliographic record

VenueFrontiers in Sociology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversité du Québec à Montréal
FundersUniversity of North Carolina Wilmington
KeywordsContext (archaeology)Resource (disambiguation)Public relationsEngineering ethicsSociologyPolitical scienceEngineeringHistoryComputer science

Abstract

fetched live from OpenAlex

In this article, we explore the challenges of conceptualizing, designing, and establishing a rapid research agenda as a local researcher following a disaster. We share what we learned while developing and implementing this rapid study and explore the challenges shaped by time pressures, our local context, and resource availability. We identify four core challenges, experienced conducting rapid research, and provide suggestions to overcome these challenges. Our goal is to provide insight to undergraduates, graduate students, and professionals who are considering rapid research inside or outside their own 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.324
GPT teacher head0.482
Teacher spread0.159 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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