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Record W2071368647 · doi:10.1177/0142064x07076306

Structure versus Agency in Studies of the Biblical Social World: Engaging with Louise Lawrence

2007· article· en· W2071368647 on OpenAlexaff
Zeba Crook

Bibliographic record

VenueJournal for the Study of the New Testament · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsCarleton University
Fundersnot available
KeywordsCollectivismIndividualismAgency (philosophy)SociologyMethodological individualismSocial worldsEpistemologyEthnographyGospelEnvironmental ethicsPhilosophySocial scienceAnthropologyTheologyLawPolitical science

Abstract

fetched live from OpenAlex

Taking Louise Lawrence’s ethnographic study of the Gospel of Matthew as a starting point, this article questions whether the structure vs. agency debate in social theory can be settled by proclaiming (or presupposing) one over the other. Indeed, sociological theory has been moving towards recognizing that society, and alongside it culture, must include both. This theoretical question matters for our understanding of the New Testament world. Can we, for instance, assume a single ratio of structure to agency for the ancient and the modern worlds? I suggest that other aspects of a culture should be brought to bear on this question, namely collectivism and individualism. Surely, a collectivistic culture (the biblical world) will operate with a different degree of structure than will an individualistic culture (North America and parts of Europe).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0160.045
Scholarly communication0.0100.013
Open science0.0010.007
Research integrity0.0040.006
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 head0.089
GPT teacher head0.432
Teacher spread0.343 · 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 source (direct Gemma or distilled Codex), 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

Citations29
Published2007
Admission routes1
Has abstractyes

Explore more

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