MétaCan
Menu
Back to cohort

Frankish military duty and the fate of Roman taxation

2008· article· en· W2115323786 on OpenAlexaff
Walter Goffart

Bibliographic record

VenueEarly Medieval Europe · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Economic and Legal Thought
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNinthMilitary serviceDutyObligationGovernment (linguistics)LawState (computer science)HistoryService (business)EconomyBusinessPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Frankish kings exacted unpaid military service from their subjects in both Merovingian and Carolingian times. The basis for this right has long been uncertain. A study of the term ‘manse’ as a Carolingian measure of assets brings to light the ostensibly hidden property on whose basis Franks went to war. This military duty reached back to the origins of the Frankish kingdom, when a large share of Roman taxes was awarded in individual allotments to soldiers obligated to serve, otherwise unpaid, when summoned, and heavily fined if they did not. Both demesne and tributary manses – contributory units – were the main part of state resources applied to military costs. They cannot be simply envisaged as components of an agricultural scheme (grand domaine). A tax‐like military obligation was one among several institutions actively surviving from the fifth century to the ninth, and it suggests that Frankish government was more law‐based and administrative than is often allowed.

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)0.004
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.026
Scholarly communication0.0060.004
Open science0.0000.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.239
Teacher spread0.219 · 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

Citations19
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueEarly Medieval EuropeSame topicHistorical Economic and Legal ThoughtFrench-language works237,207