Second elicitation round. The significant correction is Connor's own framing:
"my actual war interest is low, but unfortunately all wars are important." The
click history looked war-heavy only because world-news feeds are war-heavy, so
geopolitics-at-weight-1.0 was reading the corpus, not the reader. Statecraft is
now its own block and armed conflict is five weighted bands (anti-imperial,
US-involved, Mideast/Israel, undercovered, general) routed mainly by importance.
New: space-aerospace at 0.95, the highest-weighted block -- Connor is an
aerospace engineer. Plus science-discovery, environment-ecology,
ohio-state-politics, left-movements, anticolonial-sovereignty, far-right-watch,
political-theory. Linux/ricing/neovim folded into software-systems.
Introduces `demote` blocks, distinct from hard vetoes, for categories adjacent to
real interests: crypto/AI hype sits next to AI regulation, culture-war outrage
next to far-right-watch, true crime next to criminal-justice policy. Hard-vetoing
those would take real stories with them -- the lesson from the Europa League
story that both a substring blocklist and a cosine threshold wrongly killed.
Sources 39 -> 56, all fetched and verified: space (SpaceNews, Spaceflight Now,
NASASpaceflight, NASA, ESA, Phys.org), Linux (Phoronix, LWN, It's FOSS,
r/unixporn), left/anticolonial (Intercept, Drop Site, Tribune, African
Arguments). Rejected on inspection: nature.rss is journal metadata ("Author
Correction: ...") and sciencedaily is a press-release mill.
Embedding stays English-only, measured rather than assumed: the same story in
Spanish and English scored 0.758 and 0.600 cosine against a random-pair p99 of
0.634, so one pair was indistinguishable from an unrelated article. Italy and
Mexico are covered by English-language sources instead.
Also fixes clustering performance: centroids are held in memory across a batch
instead of one SELECT plus a numpy rebuild per item, which had taken ~15 minutes
for 1,258 items.
Ground-up replacement for news_triage, whose signal quality failed because it
had no representation of what its user likes -- three keywords fed to BM25 plus
a two-term substring blocklist.
profile/ holds the taste model as prose and TOML: 11 interest blocks, 3 veto
blocks, 5 importance blocks, each a set of probe sentences to be embedded.
The [scoring] constants are fitted, not guessed. CALIBRATION.md records the
measurements against all 3,885 items in the v0.2 database and 40 real feedback
labels, including two findings that changed the design:
- compare blocks by z-score within block, never raw cosine; raw cosine let
geopolitics win 78% of items and buried known-liked items at median rank 1246
of 3885 (293 after normalizing)
- veto needs a margin over the interest signal, not a threshold; a plain 0.55
cutoff falsely killed "Belgian mayor blocks club from hosting Israeli opponent
in Europa League", which the old substring blocklist also killed
connor