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Record W2463015236 · doi:10.5153/sro.3827

The Biographical Network Method

2016· article· en· W2463015236 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociological Research Online · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDynamismRelation (database)SociologyCosmopolitanismSocial network analysisVisualizationComputer scienceEpistemologySocial scienceArtificial intelligenceSocial capitalPoliticsLawData miningPolitical science

Abstract

fetched live from OpenAlex

This article introduces a network visualization method that enables a thorough analysis of the link between life history and social networks. Network visualizations are generally static, and as such they tend to disguise rather than uncover change and continuity within networks, and the influence that certain events may have on someone's sociability. The Biographical Network (BN) is a mixed method approach combining life story interviews with formal SNA that attempts to overcome the consequences of this lack of dynamism in network visualizations. In the first part of the article the underpinnings of the BN design and the logistics of the method are outlined in relation to a doctoral study on cultural cosmopolitanism. In the second part findings from applying the BN method with 28 young British and Spanish adults living in Madrid and Manchester are used to demonstrate its utility and its limitations for sociological analysis.

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.

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)0.007
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.004
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.272
GPT teacher head0.567
Teacher spread0.294 · 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