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Record W2616489778 · doi:10.18276/er.2015.25-01

Rola automatycznych narzędzi fiskalnych w stabilizowaniu koniunktury w Polsce w latach 2000-2014

2015· article· pl· W2616489778 on OpenAlexaboutno aff
Ryszard Barczyk

Bibliographic record

VenueEuropa Regionum · 2015
Typearticle
Languagepl
FieldEconomics, Econometrics and Finance
TopicEconomic and Fiscal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInflation (cosmology)EconomicsQuarter (Canadian coin)UnemploymentFiscal policyBusiness cycleMacroeconomicsStabilization policyEconomyMonetary policyGeography

Abstract

fetched live from OpenAlex

The aim of the study is to examine the character of the influence of automatic fiscal policy instruments on the shaping of internal stabilization of the market economy, where this stabilization involves limitation of the amplitude of business fluctuations, reduction of unemployment and restraint of the dynamics of inflation processes. The paper consists of an introduction, three parts and a conclusion. In the first part, after introductory remarks, hypotheses were formulated as concerns goals and role of automatic fiscal policy instruments in the process of stabilizing market economies. The second part presents evolution of tax fiscal instruments applied in Poland and ponders upon the question whether their influence is automatic or discretionary. The subsequent part contains the results of empirical analyses, showing the impact of automatically applied direct taxes on accomplishment of the goals of internal stabilization of Poland’s economy in the period from quarter I 2000 to quarter III 2014.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.080
GPT teacher head0.228
Teacher spread0.148 · 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
Published2015
Admission routes1
Has abstractyes

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