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Record W4404672645 · doi:10.4324/9781003342083-12

Trauma visualization

2024· book-chapter· en· W4404672645 on OpenAlexaboutno aff
Milana Nikolko, Klavdia Tatar

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMedicine

Abstract

fetched live from OpenAlex

This chapter analyses the role of transnational communities (diasporas) in the process of collecting, securing and converting episodes of national trauma into the global visual products of remembering and co-optation. Informed by memory studies and diaspora research, the study explores initiatives taken by international communities to recreate the collective narrative of trauma and change its status in the existing model of mnemonic positionality. Over the 20th and 21st centuries, the Ukrainian Canadian diaspora has become a remarkable mnemonic actor, known for championing very specific ‘symbolic’ causes that aim at generating certain images of the community for a general audience. Among them are recognition and information campaigns about the Holodomor genocide and the creation of multiple cinematic products, which reach out to Canadian and international audiences. The diaspora’s participation in the exhibit for The Canadian Museum for Human Rights was another symbolic, yet controversial, milestone for the diaspora group. Both campaigns are interconnected and have become known for their ambivalent effect on actors from the diaspora and the process of memory politicization across Canada. The research unpacks the diaspora group’s capability as a key mnemonic player amongst other competing stakeholders. The above empirical examples are investigated to show how memory politics within diaspora communities is being instrumentalized.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.942
Threshold uncertainty score0.996

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.005

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 head0.233
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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