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Record W7038377402

Get over it? The true effects of violence in the Francophone world

2018· article· en· W7038377402 on OpenAlexaboutno aff

Bibliographic record

VenueScholarly Commons (University of the Pacific) · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCaribbean and African Literature and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsFrenchIdentity (music)ColonialismIdeologyDutySubject (documents)
DOInot available

Abstract

fetched live from OpenAlex

Abstract: Get over it? Is an invitation to explore the Francophone world and the lingering effects of its unseen violence. This research project took us to four countries (Canada, Algeria, Martinique, Guinea), and explored the voice of the people, often unheard, but directly affected by French colonialism and it’s invasive forced assimilation. The measurable effects of colonialism, or the “what”, are of course data points that are easily found in economic exchange, raw resources depletion, ideological education, technology, etc... However, the unseen effects, or the “how”, on the core identity of a people is more nuanced, subtle, and yet more impactful. Findings: We intend to explore a form of violence that results in the loss of the self and the fragmentation of individualism. French colonization resulted in violent repercussions that exist in ex-colonies to this day. Violence of identity loss is unique to the individuals in each country. The French never fostered a sense of cultural cohesion, instead assimilation. Forced individuals of a country to be torn apart between two cultural, disharmonious forces. Power differential exists not only internally but on a global platform Fragmented identity results in a loss of individual power, cultural potential power, and global presence due to the self hating ingrained beliefs. Artist's Statement We were inspired to explore this subject because it is the duty of the artist to redefine our human experience and represent the voices of the past. With this in mind, we researched authors that were passionate about exposing their experiences and are little read. Uncovering the words of history helps us to overlay the lense of knowledge in our outlook of the world today. We must always remember the capacity that literature has to help us understand, and respect one another, as a part of humanity’s collective whole.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.787

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 integrity0.0000.000
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 head0.010
GPT teacher head0.179
Teacher spread0.170 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

Explore more

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