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Transparency, Technology and Taxation

2016· book-chapter· en· W2476419461 on OpenAlexaff
Richard M. Bird

Bibliographic record

VenueAdvances in public policy and administration (APPA) book series · 2016
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransparency (behavior)LegitimacyPublic economicsState (computer science)BusinessGovernment (linguistics)Tax administrationAdministration (probate law)Law and economicsEconomicsAccountingTax reformPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

Taxes and tax administration are important. Taxation is one of the main interfaces between state and society: how a tax system is administered may affect not only its yield, its incidence, and its efficiency but also the state itself. Taxation that is widely perceived to be unfair and administered capriciously and corruptly may not only bring the tax system into disrepute but weaken trust in government and even the legitimacy of the state. This paper discusses two important aspects of taxation – its ‘transparency' and the increasingly important role of information technology (IT) in tax administration, as well as how these two topics relate to the broader issues just mentioned.

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)0.004
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.006
Scholarly communication0.0070.006
Open science0.0000.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.030
GPT teacher head0.257
Teacher spread0.228 · 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
GenreOther

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

Citations3
Published2016
Admission routes1
Has abstractyes

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