MétaCan
Menu
Back to cohort
Record W1799987376 · doi:10.1017/cbo9780511619366.005

Trade and Revenue

2007· book-chapter· en· W1799987376 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

VenueCambridge University Press eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEU Law and Policy Analysis
Canadian institutionsHumber PolytechnicUniversity of Toronto
Fundersnot available
KeywordsRevenueEconomicsBusinessFinance

Abstract

fetched live from OpenAlex

Almost every country now has a VAT. But is the VAT now in place in most developing and transitional countries as good as it could be? Must ‘good’ VATs always follow the same pattern? Can every country administer VAT sufficiently well to make the introduction of the tax worthwhile? Is VAT always the best way to respond to the revenue problems arising from trade liberalization? Can VAT be adapted to cope with the rising demands in some countries, especially federal countries, for more access to revenues by local and regional governments? Can VAT deal with such new problems as those arising from changes in business practices with financial innovations and digital commerce? The answers to such questions are critical in many emerging economies. VAT is too important for them not to get the answers right – or at least as right as possible.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.968
Threshold uncertainty score0.876

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 studies0.0000.001
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 head0.046
GPT teacher head0.263
Teacher spread0.217 · 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