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Record W3209525324

SOCIOLOGY 355 -STRUCTURAL ANALYSIS

2010· article· en· W3209525324 on OpenAlexaff
Alexandra Marin

Bibliographic record

VenueTRAILS: Teaching Resources and Innovations Library for Sociology · 2010
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFriendshipSociologyPovertySocial network analysisNeed to knowPublic relationsInternet privacyPolitical scienceComputer scienceSocial scienceSocial capitalComputer securityLaw
DOInot available

Abstract

fetched live from OpenAlex

We’ve all heard it said, It’s not what you know; it’s who you know. Structural Analysis, more commonly known as Social Network Analysis, is the study of who you know, who they know, and why it matters. You will learn to describe different kinds of networks, including social support networks, workplace networks, sexual networks, organizational, friendship networks, and internet-based social networks. You will also learn why these networks matter for outcomes such as being healthy, finding a job, getting a promotion, escaping poverty, catching a cold, having a great idea, and getting other people to recognize your great idea.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2010
Admission routes1
Has abstractyes

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