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IMF Survey

2006· article· en· W4230386471 on OpenAlexaboutno aff
Dong Ng, Greg Lovett

Bibliographic record

VenueIMF Survey · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Long-term fiscal outlook is key U.S. challenge Egypt moves forward with economic reforms Canadian reforms enable more women to workThe high cost of suspending the Doha trade talksIn the past decade, Canada has seen an impressive increase in the number of women in the workforce.Much of the credit appears to go to mid-1990s reforms: family-friendly policies (improved access to quality early childhood education and care, and expanded maternity and paternity leave benefits) and lower taxes (a decrease in the secondary earner's tax wedge).To boost female participation and meet the challenges of population aging, other countries can follow Canada's example.With incomes stagnating at the beginning of this decade, Egypt in 2004 began to pursue ambitious reforms designed to help a more market-oriented economy take root.Aided by a supportive global economic and financial environment, real GDP has accelerated and investor interest has surged.But growth will have to speed up further to help employ a burgeoning, youthful workforce, and public debt must be lowered.The suspension of the Doha Round trade talks on July 24 caused barely a ripple in financial markets, but a lengthy breakdown would represent a "missed opportunity," cautions IMF trade expert Hans Peter Lankes.The world economy risks seeing an even more pronounced shift toward bilateral deals, with reduced transparency, more discrimination, and added red tape.The talks need to be rescued right away, Lankes says, or there may be years of drift.Despite tighter monetary policy, sharply higher energy prices, and a devastating hurricane season, the U.S. economy remained a key engine of global growth in 2005 and now appears to be on course for a soft landing.The country's main challenge lies ahead: if it is to ensure a sound long-term fiscal outlook, the United States must find a way to put Social Security and, especially, its Medicare and Medicaid programs on a durable footing.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.648
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.009
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0640.033

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 head0.050
GPT teacher head0.319
Teacher spread0.269 · 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 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

Citations2
Published2006
Admission routes1
Has abstractyes

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