The publication decisions for the series follow from the constraints identified earlier. AI-era institutional change moves faster than the monograph cycle, and the readers most affected by the change cannot wait for the cycle to complete.
Each paper is archived on Zenodo as the versioned record, with a persistent DOI, and disseminated through SSRN, ResearchGate, and codeafter.ai. The persistent DOI provides the scholarly record. Open access provides the reach. Version control allows the work to be updated as the subject evolves.
A v1.0 edition of the primary manuscript will be produced once the series has completed. It will consolidate the framework with the accumulated findings of the six papers and will be submitted to a major university press for formal academic publication. The sequence — open-access series first, consolidated monograph later — is not a retreat from academic ambition. It is the route to it that the subject matter permits.
The project is bilingual at the structural level, not at the translation level. English and Chinese are the two primary languages of frontier AI development. The training data, the research literature, the model documentation, and the technical discourse all run in these two languages. A project that analyses this world in only one of them captures only part of what it claims to describe. The system being analysed is already bilingual. The analysis must be as well.
codeafter.ai is bilingual English–Chinese from launch. Chinese editions of each paper are produced in parallel with the English originals through direct authorship, collaboration, or high-quality translation as circumstances permit, with cadence kept as close to the English release as production allows.
Additional language editions — Spanish, Arabic, French, Hindi, Japanese, Korean, Swahili, Indonesian, and others — will follow where the project's purposes require them and where genuine collaborators can be found. The initial selection itself is part of the project's analytical work. Rather than translate into a fixed set of high-prominence languages, the series uses each language edition as evidence about the conditions under which AI-relevant legal and institutional argument travels or fails to travel. The criteria are language family, resource tier, script system, and the presence of local collaborators positioned to extend the work. The Language paper, first of the six, will itself inform which additional languages deserve priority by naming the conditions under which the Linguistic Gap is most urgent.
Collaborators on local-language editions are acknowledged formally and credited as contributors to the series, not as translators of completed work. Local editors are responsible for reconstructing the argument in the register of their own language, embedding cases, references, and institutional context that anchor the work for local readers. They also identify, in that setting, how AI's effects are experienced, mediated, and contested — what the framework's predictions actually look like on the ground in their jurisdiction. Each local edition is, in this sense, both an output and a research site.
The publishing architecture and the layered outputs together form a system designed against latency. Analysis does not wait for translation; translation does not dilute analysis. Given that language is where institutional reach first breaks down under AI, parallel-language publishing is not a publishing strategy but a methodological premise. The Language paper will map that break in full, and will show why the erosion of linguistic sovereignty is now moving faster than most governance frameworks can perceive it.
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