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Record W4211153434 · doi:10.1017/9781108782067.007

Private Memory

2019· book-chapter· en· W4211153434 on OpenAlexaff
Justin Fantauzzo

Bibliographic record

VenueCambridge University Press eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer scienceNeuroscienceCognitive sciencePsychology

Abstract

fetched live from OpenAlex

Chapter 6 examines the private memory of ex-servicemen who fought in the Middle East and Macedonia. It uses a source not meant to influence public opinion at all: scrapbooks. This chapter makes two arguments. First, it argues that scrapbooks were spaces of private memory and, to borrow from Pierre Nora, sites of memory. British and Dominion soldiers who had photographed the war and spent most of their service in the Middle East and Macedonia had to remember the war differently. Their campaigns bore little resemblance to the conflict on the Western Front. Ex-servicemen used scrapbooks as a way of actively constructing a past that was both recognisable and acceptable to them. Some ex-servicemen pictured the war as a relentless struggle against the Ottomans or Bulgarians, and the harsh climatic and environmental conditions of the Middle East and Macedonia. Others pictured the war as an exciting episode of travel. Others still pictured the war in chronological order, slotting their personal experience of the war into the narrative. While publicly, in memoirs, ex-servicemen made a number of claims that were meant to compete with the Western Front, privately, in scrapbooks, ex-servicemen focused almost entirely on travel, tourism, and camaraderie.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.822
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.217
Teacher spread0.198 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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