Meta-Arguments in Heterogeneous Logics and How to Evaluate Them

Abstract This paper explores the problem of evaluating meta-arguments within the framework of heterogeneous logics. I introduce two new heterogeneous logics, KLP and LK3 , which are based on the interpreted languages of LP and K3 . I then present three distinct approaches to meta-argument evaluation, each aimed at preserving, in different ways, the heterogeneity of the underlying logics. Finally, I show that the second approach allows me to distinguish these new logics from others such as TS and ST , offering a more nuanced framework to address meta-argument distinctions in heterogeneous settings.

Authors

Institutions

Publication Details

Journal
Logica Universalis
Published
2025-11-04
DOI
https://doi.org/10.1007/s11787-025-00403-4
Citations
1
Primary Topic
Logic, Reasoning, and Knowledge
Type
article
Field-Weighted Citation Impact
2.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Meta-Arguments in Heterogeneous Logics and How to Evaluate Them

Christian Romero-Rodríguez
1 citations
Logica Universalis
Logic, Reasoning, and Knowledge
2.48
article

Meta-Arguments in Heterogeneous Logics and How to Evaluate Them

Christian Romero-Rodríguez
article en
1 citations

Abstract

Abstract This paper explores the problem of evaluating meta-arguments within the framework of heterogeneous logics. I introduce two new heterogeneous logics, KLP and LK3 , which are based on the interpreted languages of LP and K3 . I then present three distinct approaches to meta-argument evaluation, each aimed at preserving, in different ways, the heterogeneity of the underlying logics. Finally, I show that the second approach allows me to distinguish these new logics from others such as TS and ST , offering a more nuanced framework to address meta-argument distinctions in heterogeneous settings.

Logica UniversalisVol. 19(4)
Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 8%
Logic, Reasoning, and Knowledge
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.