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Record W2298946387

"'We Have to Keep Moving': Transnational Witnessing in Dany Laferrière's The World is Moving Around Me"

2015· book· en· W2298946387 on OpenAlexaboutno aff
Christina Kullberg

Bibliographic record

VenueDiva portal (Dalarna University Library) · 2015
Typebook
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
Fundersnot available
KeywordsWitnessSeriousnessNarrativeIdentity (music)National identityMedia studiesTheme (computing)SociologyAestheticsHistoryLawPolitical scienceLiteratureArt
DOInot available

Abstract

fetched live from OpenAlex

Dany Laferriere has never claimed to represent Haitian identity, either as a person or in his texts. Constantly moving between Haiti, Montreal, Paris, and other places in the world, Laferriere explores the idea of identity as a shifting transnational category by using strategies such as playing with his role and position as a writer both within and outside his fictional worlds. The earthquake that struck Haiti on January 12, 2010, gave his play with the authorial identity an acute seriousness, as he quickly assumed the role as an eye-witness to the disaster in international media. What happens then when someone who is notoriously known for refuting any national and cultural identity suddenly becomes the voice of the inside? Drawing on Blanchot's theories of disaster writing, on Mark D. Anderson's study of disaster and national identity and on Mads Rosendahl Thomssen's notion of world theme, the aim of this essay is to analyse how Laferriere uses his transnational experience of global movement and of being at once inside Haiti, and thereby reconfigures the notion of disaster writing. I will show how the very act of witnessing transfolds in a transnational setting which has an impact on writing itself, and I will problematise the ways in which Laferriere's writing operates as to avoid turning the disaster into an event by creating a narrative that paradoxically builds a sense of continuity through fragmentation.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.668
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
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.239
Teacher spread0.220 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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