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Record W2576990849

Efektivní sazby daně z příjmů fyzických osob ve frankofonních zemích

2011· dissertation· cs· W2576990849 on OpenAlexaboutno aff
Lenka Pokorná

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2011
Typedissertation
Languagecs
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

This work is focused on effective tax rates of the personal income tax from a microeconomic perspective. The work analyses francophone countries, namely Belgium, France, Canada, Luxembourg, Greece, Switzerland and also the Czech Republic. The first chapter defines elements of the personal income tax, social insurance contributions and the effective tax rate along with examples of its calculation. The second chapter describes the personal income tax and social insurance contributions in chosen countries and calculates the effective tax rate using collected information. The effective tax rate is calculated for six sample taxpayers with different levels of average wage. The final chapter compares, according to sample taxpayers, effective tax rates including only income tax or social security contributions payed by employees, and at the end the effective tax rate as a whole.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.004

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 head0.023
GPT teacher head0.344
Teacher spread0.321 · 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 designObservational
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

Citations0
Published2011
Admission routes1
Has abstractyes

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