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Record W4382775497 · doi:10.4000/ried.8344

Déconstruire la cartographie des relations sino-africaines : le cas des ports

2023· article· fr· W4382775497 on OpenAlexaff
Xavier Aurégan

Bibliographic record

VenueRevue internationale des études du développement · 2023
Typearticle
Languagefr
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsCentre de Géomatique du Québec
Fundersnot available
KeywordsPolitical scienceHumanitiesGeologyArt

Abstract

fetched live from OpenAlex

Cet article propose une vision critique des productions – cartographiques – universitaires portant sur les rôles chinois dans les ports africains. Pour ce faire, une contre-représentation cartographique de ces présences chinoises est générée afin de prendre en compte tout d’abord les modalités d’intervention chinoises, de déconstruire ensuite la cartographie afférente et, enfin, d’inverser les représentations et la cartographie afro-chinoise portuaire. Les résultats de l’enquête font état d’une présence chinoise multimodale qui peut être qualifiée de parcellaire, avec 55 ports et 12 ports secs africains financés, construits et/ou subsidiairement gérés par un acteur chinois, mais également 149 qui ne le sont pas.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.042
GPT teacher head0.264
Teacher spread0.222 · 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 designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

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