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Record W3155073556 · doi:10.5267/j.ac.2021.3.014

The effect of tax morale on tax evasion in the perspective of Tri Hita Karana and tax framing

2021· article· en· W3155073556 on OpenAlexvenueno aff
Ni Made Suwitri Parwati, Muslimin Muslimin, Rosida P. Adam, Chalarce Totanan, Nina Yusnita Yamin, Muhammad Din

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTaxpayerFraming (construction)Tax evasionBusinessPublic economicsEconomics

Abstract

fetched live from OpenAlex

This study aims to analyze the effect of tax morale in the Tri Hita Karana perspective and tax framing on tax evasion. The experimental design is a 2×2 between-subject which are 56 taxpayers of the Balinese people who live in Palu City, Indonesia. The tax framing variable is manipulated with positive and negative framing scenarios. Each taxpayer determines the amount of income is reported. If the taxpayer reports that his income is getting closer to the real thing, then it is stated that he is doing a lower tax evasion and vice versa. The test results indicate that in the perspective of Tri Hita Karana, taxpayers with high tax morale undertake lower tax evasion than taxpayers with low tax morale. This study also found that taxpayers with positive framing treatment performed lower tax evasion than taxpayers with adverse framing treatment. The results of this study provide evidence that increasing taxpayer compliance and reducing tax evasion can be done with high tax morale internalized in the Tri Hita Karana culture and framing information positively.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.130
Threshold uncertainty score0.212

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.022
GPT teacher head0.246
Teacher spread0.225 · 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 teacher head, 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

Citations20
Published2021
Admission routes1
Has abstractyes

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