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Record W4388439578 · doi:10.7202/1106038ar

Une crise financière qui ébranle les colonnesdu temple

2023· article· fr· W4388439578 on OpenAlexvenueaboutno aff
Rémi Moreau

Bibliographic record

VenueAssurances et gestion des risques · 2023
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Alors que les déboires des institutions financières liées au marché hypothécaire à risque (subprimes) se sont accumulés depuis plusieurs mois, l’auteur identifie d’abord quelques institutions américaines prises dans la tourmente en septembre et en octobre, une contagion qui s’est poursuivie sur les marchés européens et asiatiques. Il passe également en revue quelques solutions drastiques mises de l’avant par les gouvernements et les Banques centrales pour aider les milieux financiers, non pas tant pour sauver quelques institutions mais pour sauver le système lui-même et toute l’économie dangereusement menacée. Il examine enfin la situation de certains marchés financiers canadiens, tant en ce qui concerne le secteur bancaire que celui de l’assurance. Les institutions financières canadiennes semblent mieux se comporter que leurs consoeurs américaines. Face à la conjoncture actuelle, on s’attend à ce que le marché de l’assurance et de la réassurance se durcisse dans les mois à venir.

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.005

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 head0.065
GPT teacher head0.280
Teacher spread0.215 · 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
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
Published2023
Admission routes2
Has abstractyes

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