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Record W1652445122

Проблема боеспособности вооруженных сил США в период англо-американской войны 1812–1815 гг. И американское общество

2013· article· ru· W1652445122 on OpenAlexaboutno aff
Анна Игоревна Тимченко

Bibliographic record

VenueСовременные проблемы науки и образования · 2013
Typearticle
Languageru
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsSpanish Civil WarIndependence (probability theory)LawPolitical scienceEnthusiasmHistoryBannerNavyVietnam WarEconomic historyPsychology
DOInot available

Abstract

fetched live from OpenAlex

The author analyses the capability of the U.S. armed forces during the Anglo-American war (1812–1815), as well as the influence of the war on the American society. Beginning the war President Madison could not count on the power and strength of the U.S. army. He relied on old generals and their experience of the War for Independence. But his hopes failed. American troops were not able to invade Canada or protect their own country from invasion. The society got divided. There were “war-hawks” as well as opponents of “Mr. Madison’s war”. Anti-war sentiment was at its strongest in New England. It diminished military efficiency of the army and militia. Desertion became usual. The situation changed after a series of defeats and after Washington was captured and burnt. Patriotic enthusiasm became a common feeling. The American hymn “Star-spangled banner” was written at that period and dedicated to the defenders of Fort McHenry. The number of volunteers increased, as well as federal assignment for the army and navy. The peace treaty restored the status quo. The American society became more united. The Anglo-American war of 1812 was nicknamed “the Second War for Independence”. Strengthened defensive capacity of the American troops was among the results of the war.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.009

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 head0.288
Teacher spread0.270 · 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
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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Same venueСовременные проблемы науки и образованияSame topicAmerican Constitutional Law and PoliticsFrench-language works237,207