MétaCan
Menu
Back to cohort
Record W4200434063 · doi:10.5334/bha-662

Sharing the Spoils: The Historical use of Loans and Gifts as Collecting Methodologies for Building Biblical Archaeology Teaching Collections

2021· article· en· W4200434063 on OpenAlexaff
Julian Hirsch

Bibliographic record

VenueBulletin of the History of Archaeology · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsTrent University
Fundersnot available
KeywordsDocumentationMandateArtifact (error)ArchaeologyHistoryExcavationPalestineClassicsLawPolitical scienceAncient history

Abstract

fetched live from OpenAlex

During the first half of the 20<sup>th</sup> century, the division of finds laws of the British Mandate of Palestine and Transjordan facilitated the legal formation of large Biblical Archaeology collections throughout the United States. For Biblical Archaeologists without excavations or surveys of their own however, creating such a collection was far more difficult with the only existing formal mechanism being the often prohibitively expensive antiquities market. Primarily using the example of the Oberlin Near East Study Collection, Oberlin College’s historical Biblical archaeology collection, I argue that in this period, scholars could rely on artifact loans and gifts from their academic colleagues in order to build large teaching collections quickly and cheaply. These dispersals strengthened the social and academic ties of Biblical Archaeologists while also mitigating institutional storage problems. Whereas the export of antiquities out of Palestine was heavily regulated, once artifacts were in the United States, their legal owners could move them as they wished, accompanied by little or no documentation. As a result, while such collections formed through loans and gifts were likely common, they remain an under-documented phenomenon.

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)0.003
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.139
GPT teacher head0.305
Teacher spread0.166 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBulletin of the History of ArchaeologySame topicArchaeological Research and ProtectionFrench-language works237,207