Data stewardship affects interpretability and reuse
Metadata, provenance, accessible formats and reproducible analysis are established components of reusable scientific evidence.
Interactive research-ethics companion
Explore, challenge and apply the idea. This lab turns the Ethical Debt framework into something you can interrogate rather than simply read.
Use it to inspect the argument, test difficult objections, or perform a transparent first-pass screen of how well an animal-derived dataset may retain its future scientific value.
Three ways in
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Ask the argument
Select a question to expose the corresponding claim, its boundary, and the source material it comes from.
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Adversarial mode
The framework is more useful if it survives serious objections. These responses deliberately distinguish what is argued, what is empirically established, and what remains uncertain.
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Structured self-audit
This is a transparent screening exercise, not a validated ethical metric. Mark each dimension as protected, at risk, or unknown. Unknown is intentionally different from failure.
Used only to generate a richer AI-review prompt. This page does not upload the text.
Epistemic boundary
Metadata, provenance, accessible formats and reproducible analysis are established components of reusable scientific evidence.
This is plausible and sometimes directly observable, but it should not be presented as a universal one-to-one causal relationship for every missing field or dataset.
That is the normative proposition of Ethical Debt. The lab helps reason about it; it does not convert the proposition into a validated quantitative instrument.
Source trail
The maintained definition, provenance, conceptual lineage and public record.
Open the frameworkThe 15-slide argument from the ethical contract and 3Rs to metadata, shadow data, virtual controls and FAIR-by-design.
View the presentationThe June 2026 Neuronautix note introducing Ethical Debt as a consequence of preventable loss of animal-derived evidence.
Read the notePeer-reviewed conceptual foundation linking data stewardship and animal welfare.
Read the paper