QuantEcon / QuantEcon/lectures
Idea: a shared glossary of technical concepts and terms, held once in the pool
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- Python
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Description
Carried over from QuantEcon/meta#141, which proposed a centralised set of explanations that lectures across every series could reference. That issue is closed; the idea belongs here, because the pool model is what makes it possible.
The idea
A glossary of technical concepts and terms, held once in the pool, that any lecture in any product can reference. Not a lecture and not a series — a set of short, linkable definitions for the vocabulary our lectures assume: contraction mapping, Domar weight, ergodicity, Leontief inverse, spectral radius, stationarity, tail index, and so on.
The reader-facing goal is that a lecture can say "we assume the operator is a contraction" and link the word, rather than either re-explaining it or assuming it.
Why this belongs to the monorepo rather than to a series
Today an explanation can only live inside one series. If a concept is used in four series, the options are to explain it four times, to explain it once and have the other three link across to a different site, or to assume it. All three are bad, and the duplication is already visible in the live repos:
ifp_egm.mdexists inlecture-python.myst,lecture-dpandlecture-jaxcross_product_trick.mdexists inlecture-python.mystandlecture-dpwealth_dynamics.mdexists inlecture-python.mystandlecture-jax_static/quant-econ.bibis duplicated across at least eight repositories
That is the exact problem the pool is designed to remove: hold the canonical thing once, and let each product select it. A glossary is the smallest, lowest-risk instance of that principle — a glossary entry has no execution, no dependencies and no figures, so it is far cheaper to share than a lecture is.
It is also a genuine argument for the pool. If the monorepo can hold one definition of "contraction mapping" that four products reference, that is a capability none of the six live series can offer today, rather than a reorganisation of something they already do.
Open questions
- Where in the layout? A glossary is pool content, but it is not a lecture. Does it live under
lectures/alongside the pool, under_base/as shared infrastructure, or in a sibling directory of its own? - Per-product inclusion. Does every product get the whole glossary, or does a product manifest select the subset its lectures actually reference? The latter fits the manifest model but means the glossary needs per-entry granularity.
- Referencing mechanism. MyST cross-references work within a build. A pool glossary referenced from several products needs the reference to resolve inside each product's build, which is a question for the
_basetoolchain rather than for the content. - Sequencing. This is post-cutover work by definition — it cannot be mirrored from upstream, because no upstream series has one. Worth deciding whether it waits for the
dppilot to prove the pool, or whether a glossary is small enough to be a useful second pilot in its own right.
Not proposed here
The original issue also floated a public subdomain for this material — concepts.quantecon.org, resources.quantecon.org and similar. None of those exist and none are proposed now. If a glossary ships, whether it is a product with its own URL or a shared component included in other products is a later question.
Filed as an idea for the roadmap, not as scheduled work.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the pool layout, the per-product manifest model, and the _base toolchain; the issue also identifies duplicated files such as ifp_egm.md and _static/quant-econ.bib as context. Done means an agreed direction for glossary placement, per-product inclusion, cross-reference resolution, and sequencing after or alongside the dp pilot.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- build-system, content, documentation
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100