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Record W2616523926

The Impact of the TPP on Opening Government Procurement to International Competition in the Asia-Pacific Region

2017· article· en· W2616523926 on OpenAlexaboutno aff
Jędrzej Górski

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementInternational tradeGovernment procurementLiberalizationCompetition (biology)Government (linguistics)BusinessFree tradeGeneral partnershipTrade agreementNegotiationInternational economicsEconomicsPolitical scienceFinanceMarket economyLaw
DOInot available

Abstract

fetched live from OpenAlex

The Trans-Pacific Partnership (“TPP”) would have been by far the world’s largest regional trade agreement.  The TPP will still be of tremendous regional importance if it endures in some form following the recent withdrawal from it by the USA, and if the USA incorporates the procurement related concessions reached while negotiating the TPP into bilateral agreements. As a complex multi-theme agreement, the TPP also covers government procurement among many other issues.  While the TPP on the whole may not bring about a Copernican revolution in terms of actual trade liberalisation and market access, the TPP procurement chapter may bring about a huge change in terms of opening the TPP parties’ government procurement markets to foreign competition.  Prior to the TPP, among the TPP parties, only the USA, Canada, Japan and Singapore have been long-standing parties to the WTO Government Procurement Agreement (“GPA”) which New Zealand joined only in 2015 and Australia has been negotiating its accession. Apart from that, the scope of other public procurement liberalising international trade commitments has been very limited in the South-East Asia region and among TPP-signatories from South America, with only North American TPP-signatories having their public procurement markets previously integrated under the North American Free Trade Agreement (“NAFTA”).Public procurement relevant commitments within the Association of South-East Asian Nations (“ASEAN”) have been very limited and unclear, whereas procurement rules agreed upon by members of the Asia-Pacific Economic Co-operation (“APEC”) have been non-binding. Liberalisation of public procurement markets in the Trans-Pacific area did not gain momentum until (i) theconclusion of the Trans-Pacific Strategic Economic Partnership (“TSEP” or “P4”), being the TPP’s predecessor, and (ii)subsequent proliferation of bilateral trade agreements directly preceding the conclusion of the TPP.  Procedural provisions imposed by the TPP procurement chapter virtually copy provisions of the GPA with minor modifications only, and this convergence implies that the determination of the TPP procurement chapter’s coverage in principle emulates solutions of the GPA model (with lists of covered procurers, goods, services and construction services as well as value-thresholds, along with averaged scope of country-specific commitments).  Major deficiencies of the TPP procurement chapter’s coverage can be seen in some countries’ refusal to cover sub-central procurers (in the case of Malaysia, Mexico, New Zealand, United States and Vietnam) and utilities services (in the case of Canada, Mexico and Vietnam) as well as in extremely long transition periods (in some cases in excess of twenty years) for decreasing contract-value-thresholds of the TPP procurement chapter’s application to standard levels (in the case of Malaysia and Vietnam).  In terms of allowing non-commercial considerations in the public procurement process, the TPP procurement chapter green-lights the pursuit of sustainabilityrelated goals to an even greater extent than the GPA. At the same time, country-specific derogations accommodate extensive traditional industrial/protectionist policies, for example by allowing significant set-asides from obligations under the TPP procurement chapter (in the case of Mexico and Vietnam)

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
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 head0.017
GPT teacher head0.324
Teacher spread0.307 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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