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Record W2235954225

On Empire and Nation

2015· article· en· W2235954225 on OpenAlexvenueno aff
Dachang Liu

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsnot available
Fundersnot available
KeywordsEmpireAllegianceEmperorState (computer science)Power (physics)LoyaltyPolitical scienceConstitutionLawAncient historyHistoryPolitics
DOInot available

Abstract

fetched live from OpenAlex

There are many common features of the empire in the history, the vast land, numerous nationalities, monarch centralization, strong military power plays an important role in the maintenance of empire wide territory. The emperor was the core of the unified empire and the legal basis of empire, without the “emperor”, “country” would have collapsed. The object to whom every nation living in the empire subjected to and pledged loyalty to be the emperor. However, for the nation-state, what to give allegiance is an abstract community. In theory of law, nation state is different from the empire. But, at any times, there is no single-nation state. Most Nation-state is a combination of different proportions of nations with a priority ethnic.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.025
Scholarly communication0.0050.007
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.048
GPT teacher head0.306
Teacher spread0.258 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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