Research ethics
Studies involving people are reviewed before data collection by the ethics commission of
the institution that hosts them. For work at Kryvyi Rih State Pedagogical University, where
most of the laboratory's members hold their appointments, that is the Research Ethics
Commission of Kryvyi Rih State Pedagogical University — a standing collegial
body chaired by the vice-rector for research and appointed by the rector for a three-year
term. Its membership spans at least five faculties and includes a lawyer, a psychologist, a
student representative and, where one agrees to serve, an external expert, so that a proposal
is not reviewed only by people who share its assumptions. The commission works to the Law of
Ukraine on Scientific and Scientific-Technical Activity, the Law on Higher Education, the
Ethical Code of the Ukrainian Scientist and the Declaration of Helsinki.
An application states the aims and methodology, who the participants are — separately
identifying minors, students, teachers, parents and people with special educational needs
— the physical, psychological, social and economic risks and how each is mitigated, the
form of informed consent, the confidentiality measures, how long data are kept and who may
access them, and any conflict of interest. Reviewers are assigned on registration, the initial
review takes ten working days, and a reasoned decision follows within thirty days: approved,
approved with minor comments, returned for revision, or refused. Approval is a precondition
for starting, and a substantive change to the protocol goes back to the commission.
The commission’s governing regulation is an internal
university document and is not published online; it can be requested from the university.
Use of generative AI
The laboratory builds and evaluates generative models, and it also uses them in its own work.
Both are governed by one principle: a generative model is an instrument, and the named
authors carry complete responsibility for everything the work asserts.
- Where a language model contributed to generating ideas or drafting text, the paper
discloses it — naming the model, its version and its source — in the methods or
acknowledgements, not in a footnote after the fact.
- A model is never listed as an author. Authorship requires accountability, which a model
cannot hold.
- Every factual claim and every citation a model produces is verified against the source
before it is used. Fluent output is not correct output; that is the premise of our own
benchmarking work.
- Generative models are not used to fabricate or augment research data, to manufacture
results, or to process participants’ personal data.
- Manuscripts under peer review are not submitted to third-party models, because doing so
discloses another author’s unpublished work.
The workshop series the laboratory organises apply the
CEUR-WS policy on
generative AI to every submission, and the Academy’s journals follow the
COPE guidance on
publication ethics.
Personal data
Participants take part on informed consent, with parental or guardian consent for minors.
Responses are coded on collection, and only de-identified data are deposited: no names, no
contact details, no dates of birth, no identifiers that could re-identify a participant in
combination. Where a dataset cannot be de-identified without destroying its research value it
is not published, and the paper says so rather than quietly omitting the deposit.
The same rule governs this website. It carries professional information only — name,
degree, academic title, position, institution and public research identifiers — and
institutional contact addresses rather than private ones.
Licensing and preregistration
Datasets are released under CC BY 4.0 (one earlier deposit is
CC BY-ND 4.0, marked as such in the list above); the Moodle filters are
GPL 3.0 or later; the content of this site is CC BY 4.0. People
are identified by ORCID and organisations by ROR so that a deposit can be attributed without
relying on name matching.
The two projects funded from 2026 commit to preregistering their study protocols on
OSF before data collection begins, and to depositing the resulting data openly. We
state that as a commitment made in the funded proposals, not as a completed record: the
laboratory has no preregistration to point to yet, and this page will link them when it does.