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Record W2769600961 · doi:10.11647/obp.0122.08

8. Bureaucracy and Knowledge Creation: The Apothecary Chancery

2017· book-chapter· en· W2769600961 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen Book Publishers · 2017
Typebook-chapter
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of CambridgeLeverhulme Trust
KeywordsApothecaryBureaucracyGunpowderPolitical scienceLawHistoryClassicsArchaeology

Abstract

fetched live from OpenAlex

Here, Griffin considers the extent to which, in the 17th century, a chancery established for the benefit of the Tsar and his family – the ‘Apothecary Chancery’ – could and did, albeit to a limited extent, generate knowledge for somewhat wider distribution. The chancery produced reports, covering a range of subjects, which included autopsies to establish cause of death, “physicals” of servitors to see if they were still fit to serve, investigations into the private trade in medical drugs, proposed courses of treatments, notes regarding unsuccessful treatments, and considerations of illnesses, medicines, and medical practices. Griffin uses these reports to investigate knowledge circulation and information technologies in the context of seventeenth-century Russian administration, and in turn to see what the Russian case can reveal about information technologies in the early modern context.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0070.005
Open science0.0110.006
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 head0.040
GPT teacher head0.287
Teacher spread0.247 · 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