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Record W1847865277 · doi:10.1080/13648470.2015.1081670

Community centrality and social science research

2015· article· en· W1847865277 on OpenAlexafffund
Dan Allman

Bibliographic record

VenueAnthropology and Medicine · 2015
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersEconomic and Social Research CouncilCanadian Institutes of Health ResearchHealth Canada
KeywordsCentralitySociologyContext (archaeology)Network sciencePublic relationsCommunity buildingPolitical scienceComputer scienceGeographyComplex network

Abstract

fetched live from OpenAlex

Community centrality is a growing requirement of social science. The field's research practices are increasingly expected to conform to prescribed relationships with the people studied. Expectations about community centrality influence scholarly activities. These expectations can pressure social scientists to adhere to models of community involvement that are immediate and that include community-based co-investigators, advisory boards, and liaisons. In this context, disregarding community centrality can be interpreted as failure. This paper considers evolving norms about the centrality of community in social science. It problematises community inclusion and discusses concerns about the impact of community centrality on incremental theory development, academic integrity, freedom of speech, and the value of liberal versus communitarian knowledge. Through the application of a constructivist approach, this paper argues that social science in which community is omitted or on the periphery is not failed science, because not all social science requires a community base to make a genuine and valuable contribution. The utility of community centrality is not necessarily universal across all social science pursuits. The practices of knowing within social science disciplines may be difficult to transfer to a community. These practices of knowing require degrees of specialisation and interest that not all communities may want or have.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.008
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.771
GPT teacher head0.663
Teacher spread0.108 · 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 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

Citations14
Published2015
Admission routes2
Has abstractyes

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