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Record W2785253444

Caen Controversy: The Battle for Sword Beach 1944

2014· book· en· W2785253444 on OpenAlexaboutno aff
Andrew Stewart

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSWORDBattleHistoryAncient historyEngineering
DOInot available

Abstract

fetched live from OpenAlex

On 6 June 1944 British, American, Canadian and French troops landed in Normandy by air and sea. This was one of the key moments of the Second World War, a long-anticipated invasion which would, ultimately, lead to the defeat of Nazi Germany. By the day’s end a lodgement had been effected and Operation OVERLORD was being hailed as a success. In reality the assault had produced mixed results and at certain points along the French coastline the position was still far from certain. The key Allied objectives had also not been captured during the first day of the fighting and this failure would have long-term consequences. Of the priority targets, the city of Caen was a vital logistical hub with its road and rail networks plus it would also act as a critical axis for launching the anticipated follow-on attacks against the German defenders. As a result an entire brigade of British troops was tasked with attempting its capture but their advance culminated a few miles short. This new book examines this significant element of the wider D-Day operation and provides a narrative account of the operations conducted by 3 British Infantry Division. It examines in some detail the planning, preparation and the landings that were made on the beaches of Sword sector. To do this it considers the previously published material and also draws upon archival sources many of which have been previously overlooked to identify key factors behind the failure to capture the city. Its publication coincides with the 70th anniversary of the Allied liberation of France.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.252
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.290
Teacher spread0.269 · 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 teacher head, not a consensus.

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

Citations27
Published2014
Admission routes1
Has abstractyes

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Same topicVietnamese History and Culture StudiesFrench-language works237,207