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Record W7075359503

Study of Strategic Narratives: The Case of BRICS.

2017· article· en· W7075359503 on OpenAlexaff

Bibliographic record

VenueRePEc: Research Papers in Economics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsNarrativeCONTESTBattleChinaNarrative inquiryIdentity (music)
DOInot available

Abstract

fetched live from OpenAlex

In the battle of narratives to give meaning to the international system in the twenty-firstcentury, emerging powers are actively engaged. In particular, the BRICS group, comprising Brazil, Russia, India, China and South Africa, have advanced their claim to reconstitute international affairs to make it more just and fair. What if their narratives about the international system effectively contest narratives constituting the Liberal World Order? For understanding the battle more profoundly, this study examines the strategic narratives of the BRICS. A documentary methodology was employed to elicit themes and narratives in BRICS joint communiqués of 2009 to 2016 for the identification of its strategic narratives. I have identified a system narrative of global recovery, an identity narrative of inclusive participation and an issue narrative of infrastructural development. A narrative grammar was used to relate BRICS strategic narratives with their narrative environment of symbolic, institutional and material practices. Due to a partial compliance with the narrative grammatical rules, the BRICS group may not effectively influence and gain public support.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0220.026
Scholarly communication0.0100.008
Open science0.0020.010
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.049
GPT teacher head0.347
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2017
Admission routes1
Has abstractyes

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