China suppressing ethnic, cultural, and linguistic diversity for homogeneity has caused immeasurable suffering and imperialistic destruction.

EU explicitly embracing ethnic, cultural, and linguistic diversity for heterogeneity has brought more peace and prosperity than ever before to a continent in perpetual conflict for nearly all of human history.

Another great example of the perverse idea that “same == better”

So would dogs see little humans or little dogs? We can't say for sure. But the best guess might actually be most likely little dogs, or maybe little smells of little dogs. Dogs show conspecific preference (species-focus) while we show facial preference [2] and they have a strong focus on olfactory sense while we're more visual. The vividness might show up in ways we can't really perceive through smell like they can.

And the answer to "does that mean the fungus has targeted humans genetically" is almost definitely no. The study the article is based on [3] mentions that lilliputian hallucinations predate this mushroom, appear across cultures' folklore, and are reported in alcohol withdrawal, dementia, and macular degeneration. The effect seems fundamental to how the human mind and brain work. So it's more likely that the mushroom is disrupting something and the brain is resolving that disruption into little people, because that's what it does with pattern matching.

This mushroom is an ectomycorrhizal symbiote of the Yunnan pine tree, is ancient with the genus being at least 5 million years old compared to modern humans 300k, and requires undercooking which isn't compatible with human targeting so it doesn't make sense to have any genetic human target.

The fungus supplies a non-targeted disruption and the resulting little people content we describe is the human brain's response. A dog getting the same disruption would resolve it into whatever a dog's machinery produces, or maybe they metabolize it into nothing recognizable.

Pretty damn cool.

[1] https://consciousnesslibrary.org/research/29070-correlation-... [2] https://www.jneurosci.org/content/40/43/8396 [3] https://consciousnesslibrary.org/research/27751-phylogenomic...

As I understand, it uses Postgres's "FOR UPDATE SKIP LOCKED" job claim feature. I don't run most jobs concurrently because they need to build on each other. Postgres advisory locks sit on top for mutual exclusion and solid_queue handles queuing. It's akin to good_job which is the pg-native thing from before solid_queue existed, but I just stuck with the easy Rails default and this is the first time I've even thought to remember how it works.

Search observation: What you're noticing with search is the currently intended behavior, but you raise an interesting point. I'm using tsvector for Postgres full-text search over title, abstract, etc. with prefix matching, specifically in English. The stemmer doesn't decompose Sanskrit so "brahmavihara" and "vihara" are separate tokens matching legitimately separate papers. Then it falls back to the embedding geometry to search by meaning instead of strings.

That said, there's enough Sanskrit going on in contemplative papers that a synonym/variant layer for Pali and Sanskrit vocabulary is a pretty good idea. There's a lot of German and Portugese in the corpus as well, so upgrading the search to account for all these languages is a great feature idea.

Tech question: There's actually zero LLM involvement at all regarding citations or references in this project. That all comes from OpenAlex API. LLMs only do relevance gating, study detail abstraction, and evidence synthesis summaries.

Google has a moat in the sense they have no API and don't license anything to anyone, so nobody builds on it and the open ecosystem of sources I'm using is the same as what AI products use. Gemini is trained on the same sources this library uses (and recently, this library itself) and the Google Scholar vault is in my opinion, pretty useless given the open ecosystem available.

Research question: the most mind-blowing results I've discovered are in an unexpected direction - it is wild how thin and low-confidence the evidence is for basically any claim regarding psychedelics, due primarily to functional unblinding and low sample size and diversity. The hype cycle is way beyond science can keep grounded.

Here's an example (disclaimer, it's my own published research!): A recent study reported an effect size for mebufotenin exceeding the theoretical maximum for antidepressants, implying methodological issues account for the results. https://consciousnesslibrary.org/research/52248-blinding-int...

Another "mind-blowing" observation is the sheer volume of consciousness work outside the psychedelic hype cycle. A full half of the corpus is on meditation or philosophy of mind, not related to psychedelics. And we still are so far from understanding the "hard problem.

Development question: I have plans to extend this indefinitely, and your factoid idea is interesting. The "study at a glance" might have most of what you're asking about already on each article, but taking that a step further, it could be cool to have a cross-corpus browsable feed of those. I'll also be integrating data from a project by Josie Kins (maker of https://effectindex.com) on psychedelic substance topics in particular for dose info and potentially trip reports, but that's a little orthogonal to what you're suggesting.

Let me know if you mean something more about factoids than the "study at a glance" and the potential to have those be aggregated in a browsable way and I'll see what I can think of.

I haven't bit off more than I can chew yet, my plan is to work on it until that's the case OR there's just nothing left to do in the scope of the project.

Thanks a lot for your comment!

On experience reports - I decided to keep it purely academic at first but will soon be working on integrating data from a tool by Josie Kins (the maker of https://effectindex.com).

I also don’t know of anywhere that aggregates reports from meditation and dreams etc, but that’s a really interesting idea. Maybe this can be the place!

That said, I've been working with Josie Kins who runs https://effectindex.com/ and she's been building out a new system that incorporates categorized subjective effects on psychedelics, dosage and harm reduction info, with a huge amount of trip reports from all over the internet that we'll integrate into the individual topics sections probably in the next couple months.

As for why I chose Rails - I just know Rails really well. I've been using it since 2012 or so, and it's basically muscle memory now. The most intensive parts of the app really would lend themselves to Python tooling and I did end up hand-building a lot of the data engineering stuff that there for sure exist plugins for in Python, but the trade off of using what I know well outweighed that by a lot. Plus the rest of it are perfectly CRUD-able server-rendered pages. Pretty Railsy aside from the data eng stuff.

I also started this before AI coding harnesses were available. I shelved it for a long time after the initial few rounds, but the work I did in the beginning was substantial enough to not just start over. If I had Claude Code with Fable when beginning, it might look a lot different. But I do like knowing everything about what I built and understanding every line.

On your AI ethics question... I do think it's possible, eventually. That's why I hedged a bunch on it being a long term goal. If open weight models gain steam and hardware acquisition becomes manageable, it would be a dream to run a self-hosted self-trained model in my house (which is powered by solar, so the renewable thing is real). It is especially realistic if some funding comes through for hardware.

I just finished my master's in Psychedelics and Consciousness Studies, and built the library I wanted while studying. I started it over a year ago, but put it down until my practicum advisor suggested I dust it off and go hard on it during my last term.

As of this writing, there are over 35,700 papers by over 82,200 authors organized into 37 topics, growing daily. There's a 2D map of the whole corpus and evidence syntheses on the topic pages, plus the ability to generate your own syntheses with any prompt.

It's built with Rails 8.1, uses one Postgres (for full-text search, vectors, and job queue), and runs on a $24/mo DigitalOcean droplet that I just upgraded from the $12 tier and deploy to with Kamal. Total LLM spend so far is ~$28 in DeepSeek-V4-Flash, trending down after a big one-time backfill push.

Relevance was the hardest part to get right by far. Ensuring we keep papers on LSD the psychedelic vs Lumpy Skin Disease, or Ketamine for depression vs anesthesia in cats was no small feat. The design ended up being a cheap keyword prefilter, then an LLM rubric that accepts or rejects papers. More on that here: https://consciousnesslibrary.org/docs/article-pipeline.html

It's free, no ads, no signup to read anything, and a registered 501(c)(3) I fund myself for now. I'd really like to know what breaks or any other feedback, and would love to answer any questions about it!

I just finished my master's in Psychedelics and Consciousness Studies, and built the library I wanted while studying. I started it over a year ago, but put it down until my practicum advisor suggested I dust it off and go hard on it during my last term.

As of this writing, there are over 35,700 papers by over 82,200 authors organized into 37 topics, growing daily. There's a 2D map of the whole corpus and evidence syntheses on the topic pages, plus the ability to generate your own syntheses with any prompt.

It's built with Rails 8.1, uses one Postgres (for full-text search, vectors, and job queue), and runs on a $24/mo DigitalOcean droplet that I just upgraded from the $12 tier and deploy to with Kamal. Total LLM spend so far is ~$28 in DeepSeek-V4-Flash, trending down after a big one-time backfill push.

Relevance was the hardest part to get right by far. Ensuring we keep papers on LSD the psychedelic vs Lumpy Skin Disease, or Ketamine for depression vs anesthesia in cats was no small feat. The design ended up being a cheap keyword prefilter, then an LLM rubric that accepts or rejects papers. More on that here: https://consciousnesslibrary.org/docs/article-pipeline.html

It's free, no ads, no signup to read anything, and a registered 501(c)(3) I fund myself for now. I'd really like to know what breaks or any other feedback, and would love to answer any questions about it!