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Record W7149458694 · doi:10.17132/2693-3179.1325

Canada: Private-Sector Term Purchase and Resale Agreements

2022· article· en· W7149458694 on OpenAlexaboutno aff
Priya Sankar

Bibliographic record

VenueJournal of Financial Crises · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)PaymentKey (lock)Government (linguistics)

Abstract

fetched live from OpenAlex

With Canadian banks curtailing their funding in response to the Global Financial Crisis, liquidity dried up in money markets and bond markets. On October 14, 2008, the Bank of Canada (BoC) announced its first Private-Sector Term PRA facility to provide liquidity to large money-market participants, such as asset managers, who were not traditional BoC counterparties and could not access the BoC’s other emergency liquidity facilities (“PRA” is short for purchase and resale agreement, similar to a repo). The program accepted commercial paper, asset-backed commercial paper, and bankers’ acceptances as collateral. It complemented the BoC’s Term PRA for primary dealers (the “regular Term PRA”), which the BoC extended to major banks on the same day. The BoC was prepared to allocate CAD 1 billion (USD 0.8 billion) to weekly auctions for the Private-Sector Term PRA, but only CAD 25 million (the minimum amount) was taken up in any single week. On February 23, 2009, the BoC replaced this facility with its second Private-Sector Term PRA. The second facility added investment-grade corporate bonds as eligible collateral and expanded the list of eligible participants. The two Private-Sector Term PRAs saw much less use than the regular Term PRA, ultimately peaking at about CAD 3 billion outstanding in mid-2009. The BoC allowed the facility to expire on October 27, 2009.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.632

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.025
GPT teacher head0.275
Teacher spread0.250 · 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
Published2022
Admission routes1
Has abstractyes

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