The name is the definition. Everything in this Preview is read out of it — nothing is added on top of it.
Read the three parts of the name plainly first. Structure, Study, funding and infrastructure language all come after that, not before it.
Three parts, each with a plain working meaning. No new meanings are invented here; this is what the name already carries.
Young people begin by finding and owning their own expression, and from there become able to encounter others. Being able to meet others follows from having something that is genuinely theirs — nothing is required of them first.
People, places, generations, bodies of knowledge, lived experience, communities and practices can remain distinct while entering into relation. Connected, not collapsed into one.
Not one narrative spoken on everyone's behalf, but many people expressing and carrying what is theirs.
Supporting interpretation, internal: YuCROWN does not tell the world's stories for people — it helps more people express what is theirs, remain author of it, and become encounterable by others. Not a slogan.
The work that already exists came out of the name in this order. It is a description of how YuCROWN developed — not a route any person has to walk.
Helping young people express what is theirs, and be seen through their own work rather than through a description written about them.
Being seen widens into seeing: asking, listening, and carrying lived experience across generations.
Across people, places, generations, practices and contexts — in real places, with real communities, around real questions.
Earth Library, C// and Study are what this growth has settled into so far — not a brand story written afterwards.
How the understanding widened over time. Never a required progression for a person, and never a slogan.
這是理解加深的過程，而非每個人必經之路。
Earth Library, C// and Study sit side by side. None is subordinate to another. C// is not part of Study. Study is not a later stage of Earth Library.
Parallel, not sequential. There is no Earth Library → C// → Study pipeline.
Each realm has its own way in, and they do not chain together automatically. No path is required before another.
A person contributes independently made work — a Station, a project, a record of practice — with authorship and context attached. Earth Library is not a Fellow program, not a learning program, and not limited to youth.
C// is distinct from Study. It begins with a young person's own expression, and may extend — never by requirement — into conversation and the field.
A selected participation path for young people, under defined Fellow rules. The current path is mainly YuCROWN invitation, with review. An emerging future path: a young person creates their own introduction and work as a Station and Casts it to a dedicated Fellow mailbox for YuCROWN review.
Not an application path. YuCROWN identifies a conversation or relationship worth creating, and invites participants to ask, listen, and carry lived experience across generations.
Real-world participation with places, practices, organizations, nature and communities. Entry depends on the specific field or project. Not automatically part of Study.
Study's door is a conversation about a real context. A school, nonprofit or community tells YuCROWN what is particular about their place, their learners, their practice or their question — and together they look at what is worth exploring. It is co-exploration, not admission to a fixed program.
Becoming an Earth Library contributor does not automatically make someone a C// Fellow — review and selection remain part of C//. Funding is a separate, outward movement, never an entry path.
AI is changing how people learn, make, express and decide. The important question has shifted: not only how people learn to use AI, but what should remain human when AI increasingly participates in how we learn, create, express and decide.
These concerns are already constant across every realm. Study is where they are now asked explicitly, in relation to AI.
Protects authorship and context.
Begins from a person's own expression and body of work.
Enables listening and encounter.
Connects people with real places and communities.
Can ask what should remain human as AI enters learning, making, expression and decision-making — explicitly, and with evidence.
“Learning & Research” rather than “Education & Research”: YuCROWN is not positioning itself as an education authority delivering a fixed AI course. “Program” may remain an internal structural concept, but it should not dominate how this is named.
Cali is responsible for helping make Human-Centered AI Learning & Research real as a framework and methodology — not for delivering a generic AI-skills course. The curriculum is not finished, and should not be described as if it were.
One shared framework, adaptable to different learners and contexts — not fixed to one population, one school or one funder.
If a school, nonprofit or community has a distinctive place, group of learners, culture, learning practice, accessibility context, language, relationship with nature or community — or a real question worth exploring — YuCROWN wants to hear about that context.
Review stays real, but it stays internal. The participation flow should feel like co-exploration, not admissions or grant bureaucracy. A conversation does not guarantee a Project, and a Project does not guarantee funding.
If there is a meaningful fit, YuCROWN and the organization shape a Project together.
The need comes first in all three. Funding never invents it.
YuCROWN identifies a real context or opportunity, looks at fit, and shapes a Project around it with the people there.
A school, nonprofit or community describes their context. If there is a meaningful fit, the Project is shaped together.
A funding or partner opportunity is checked against existing mission, contexts, framework and Projects. A need is never invented to fit funding.
Human-centered AI, human agency, critical thinking, authorship, responsible human–AI collaboration and human-centered learning appear to be growing in importance across education, research, policy and funding landscapes. This is useful framing for Cali, for OS and for funding work.
No external organization endorses YuCROWN, and no statistics, reports or institutional positions are asserted here. Treat the paragraph above as a working landscape hypothesis. Any external fact, figure, framework or citation must be sourced and verified before it appears in a proposal, a public page or a funder conversation.
The starting point is never “what AI grant can we apply for?” It is the question, the people and the context. Funding helps a Project happen; it does not define the need and does not define the mission.
Lenses for recognising where a real Project might meet a funder's own concern — not a directory.
Funder names, deadlines, amounts, eligibility, application links, status and next actions belong in the OS — not in this Preview.
The Fengshan school proposal is one rural / place-based direction being explored — a possible application of the framework, not a confirmed commitment, and not evidence of confirmed funding.
EarthLinC is not claimed here to be the best protocol. That is a hypothesis YuCROWN can test through real Projects. What can be stated is why it may be particularly suited to Human-Centered AI Learning & Research.
Typical AI interaction collapses attention onto two visible points: prompt → AI output. Everything human around it disappears.
This whole process is what YuCROWN needs to preserve around AI-assisted work — not only the final artefact.
An enabling protocol that can support Earth Library, C// and Study without becoming any of them — and so a participant does not only attend, but may leave with work that remains theirs.
Can EarthLinC help make the human process visible again around AI-assisted work?
Kong Group develops and supports EarthLinC and provides YuCROWN with technical support and in-kind credits. Where a genuine public-benefit Project creates a real technical need, that need can inform capability development. The direction is always human and project need → technical capability — never technology → find people to promote it.
Status language keeps this Preview honest about where each part actually stands.
Define the Human-Centered AI Learning & Research framework: methodology, inquiry areas, evidence and evaluation, and how distinct Projects can adapt it without becoming a fixed curriculum.
Operationalize schools and contexts, conversations, project formation, funding research, funder fit, applications, status, next actions, evidence and outcomes.
Later, once this internal synthesis is stable, update public language, the three-realm structure and the participation paths — including “take part in the Study”.
Identify the protocol capabilities that real Study Projects demonstrate are actually needed — capability follows demonstrated need, not the reverse.
A working synthesis. The next version should be written against what actually happens.