Envíos

Semantics of typed indeterminacy

Formal semantics that distinguish kinds of non-determination, including annotated, paraconsistent, many-valued and evidence-based logics. Contributions require a precise, relevant formal result, complete proofs and an explicit interpretation or example. Measurable implications are welcome where appropriate; a formal illustration is not empirical validation. Positive, negative and limiting results are eligible under the common assessment criteria.

Abstention and risk-coverage

Selective prediction, reject options and abstention, evaluated through risk-coverage behaviour rather than accuracy alone.

Disagreement as signal

Human and machine disagreement treated as information: label variation, inherent disagreement, and insufficient versus contradictory evidence.

Belief revision and epistemic update

Operators for belief change and epistemic update, their formal properties, and the conditions under which they predict observable behaviour or inform decisions. Formal results require complete proofs and an explicit interpretation or example; empirical claims require operational definitions, appropriate comparisons and reproducible analysis. Positive, negative and limiting results are eligible under the common assessment criteria.

Audit of uncertainty frameworks

Reproducible audits of how uncertainty frameworks are applied, including reanalyses of published studies.

Decision under indeterminacy

Decision methods that use incomplete, indeterminate or contradictory evidence, with explicit comparisons against appropriate alternatives for the task. These may include classical, probabilistic, calibration, selective-prediction or established decision methods. Comparisons must use fair access to information and distinguish representational, predictive and decision advantages. Positive, negative and limiting results are eligible under the common assessment criteria.

Negative results

Calculi that separate nothing and distinctions that collapse under measurement, reported with the same rigour as positive results.

Evidential reasoning in educational and social measurement

Applied studies in education and the social sciences that test whether, when and how distinguishing lack of evidence from conflicting evidence changes a measurement or a decision. Typical settings: expert judgement for validating instruments (for example Aiken's V), panels and rubrics with several assessors, perception surveys (indifference versus ambivalence), Delphi studies, evidence coding in literature reviews, and institutional decisions.

Requirements.

• Real data. Simulated data are accepted only when declared as such.
• A comparison with the standard tool for the case: mean and standard deviation, Krippendorff's alpha, Aiken's V or the Thompson, Zanna and Griffin ambivalence index.
• Data and code available, with the measurement or decision rule and analysis protocol fixed before examining confirmatory data. Clearly label exploratory analyses, reanalyses, reused data and any deviations from the protocol.
• Engagement with the literature on attitude ambivalence (Kaplan, 1972; Cacioppo and Berntson, 1994; Thompson, Zanna and Griffin, 1995). Measuring agreement and disagreement separately is not new, and submissions should not present it as a new method.

Article types. Research articles with real data (for example, the original scale and its two-question version applied to the same respondents), reanalyses of existing data with open data and code, tutorials, negative results and registered reports.

Not considered. New operators illustrated only by a ranking on a numerical example; triplets that a language model reports about itself presented as measurements; synthetic data presented as real.

Positive, negative and limiting findings receive the same common assessment criteria. Claims of equivalence require a justified margin and suitable analysis; lack of statistical significance alone is insufficient. Validation of AI or language-model assessment must distinguish item, prompt, threshold and population sensitivity and use appropriate established measurement comparisons.

This section is limited to one third of the articles in each issue.