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Record W2118485340 · doi:10.1111/1467-9701.00350

India's Trade Policy Reforms and Industry Competitiveness in the 1980s

2001· article· en· W2118485340 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWorld Economy · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsConcordia University
Fundersnot available
KeywordsEconomicsComparative advantageShadow (psychology)Shadow priceUnit (ring theory)Manufacturing sectorInternational economicsMacroeconomicsInternational trade

Abstract

fetched live from OpenAlex

The paper proposes a method of measuring and analyzing competitiveness, and applies it to Indian manufacturing data of 1980/81, 1987/88 and 1991/92. The method consists of computing a unit cost ration and breaking it down into various components, ditinguishing between comparative advantage measured at shadow prices, and competitive advantage measured at market prices. The difference, equal to the sum of all price ditortions, may enhance or diminish competitiveness, depending on whether the distortions are cost‐increasing or ‐decreasing. The study reviews first the limited trade reforms of the 1980s and examines whether they have led to increased competitiveness. Although the present study is limited to less than the full potential of the method, due to lack of adequate data, it demonstrates, that the policy changes of the 1980s have failed to enhance the competitiveness of the industrial sector as a whole, while some industries have undergone substantive changes. In three industry case studies the results are compared with the findings of earlir studies.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.556
Threshold uncertainty score0.707

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 studies0.0000.000
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 head0.040
GPT teacher head0.224
Teacher spread0.185 · 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