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Record W4401538535 · doi:10.56294/sctconf20231064

Knowledge and contribution against tax fraudation on the local economy in Guayaquil

2023· article· en· W4401538535 on OpenAlex
Vanessa Josefa Hernández-Alvarado, Jenory Nicole Becerra-Campi, Alexander Josué Bajaña-Jiménez, María Barragán Gáleas

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

VenueSalud Ciencia y Tecnología - Serie de Conferencias · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsCarré Technologies (Canada)
Fundersnot available
KeywordsTax evasionPaymentBusinessPopulationGovernment (linguistics)Service (business)EconomyPublic economicsEconomicsFinance

Abstract

fetched live from OpenAlex

Tax evasion by taxpayers and companies constitutes a frequent crime in different economies, which indirectly impacts the local economy of any territory. In the city of Guayaquil, during the year 2022, the crime of tax fraud has been a growing concern, taking into account the impact this has on the local economy. The population of this area has seen the greatest impact reflected in public services due to their lack of attention and the decrease in the resources necessary to provide a good service to the general population. The existing situation with the lack of combativity, access to information and the population's low awareness of the issue could be verified through the study of a sample with the application of instruments that allowed it. The results obtained are evidence that tax fraud affects the economy and attention of society. The government has regulations regarding tax contributions and obligations for everyone in general, but at the same time, it lacks strict control over compliance with payments, which is why fraud by companies is common.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.039
GPT teacher head0.233
Teacher spread0.194 · 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