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Record W3125442621 · doi:10.3167/hrrh.2021.012001

Apprenticeship and Learning by Doing

2021· article· en· W3125442621 on OpenAlexvenueno aff
Jeff Horn

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsApprenticeshipGuildTraining (meteorology)Formal educationPolitical scienceEconomyManagementSociologyHistoryGeographyArchaeologyEconomicsPedagogyEcology

Abstract

fetched live from OpenAlex

In France, formal guild training was not as ubiquitous a means of socializing young people into a trade as it has been portrayed by scholars. Guilds were limited geographically, and in many French cities privileged enclaves controlled by clerical or noble seigneurs curbed the sway of corporate structures, or even created their own. Eighteenth-century Bordeaux provides an extreme example of how limited guild training was in France’s fastest-growing city. The clerical reserves of Saint-Seurin and Saint-André that housed much of the region’s industrial production had quasi-corporate structures with far more open access and fewer training requirements. In Bordeaux, journeymen contested masters’ control over labor and masters trained almost no apprentices themselves. Formal apprenticeship mattered exceptionally little when it came to training people to perform a trade in Bordeaux.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.032
Scholarly communication0.0090.006
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.035
GPT teacher head0.260
Teacher spread0.225 · 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 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

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