Phase 1 findings — sect classifier v0 (firdaria × significators)¶
Date |
2026-07-11 |
Verdict |
NO-GO — firdaria-lord matching does not recover sect |
Code |
|
Spec |
The experiment¶
Blank each of the 63 corpus people’s birth time; predict day vs night from their dated events alone, by matching the active firdaria time-lord (day-order vs night-order) to each event’s natural planetary significators (theory §6). This is the pre-registered proving experiment: does the approach beat chance?
Result¶
Variant |
Accuracy |
Notes |
|---|---|---|
Raw day-vs-night sums |
49.2% |
strong night bias (predicted night 43/63) |
Permutation-null de-confounded |
41.3% |
bias gone, balanced confusion, still chance |
Best achievable (any threshold, any ablation) |
54.0% |
= majority class (“always day”) |
95% CI (de-confounded) = [30%, 54%] — straddles 50%.
corr(continuous signal, true sect) = −0.17 to −0.22 across all variants — slightly negative, ≈ 1.7 SE from zero at n=63, i.e. indistinguishable from no signal.
Ablations (major-lord-only, major-events-only, ± sub-lord) all land at the majority-class 54%. The null is robust.
Pre-registered gate (acc ≥ 65% AND CI-low > majority): NO-GO.
What we learned (the diagnosis)¶
The raw comparison is confounded. The night firdaria order front-loads Saturn/Jupiter/Mars in the event-dense early decades, and those are the generically-significant planets (Saturn signifies 8/15 event types). So the night ordering scores higher for anyone, regardless of true sect — a nuisance factor, not sect signal. A per-person permutation null removes it cleanly.
De-confounded, there is simply no signal. Firdaria periods are long (7–13 yr), so a documented life samples only ~5–7 distinct major lords — very few “measurements” of a type↔lord association that is itself weak. Firdaria lacks the resolution to fix sect.
This is a clean, cheap result: the shortcut of reading sect off firdaria alone — appealing because it’s near time-independent — does not work. Better to know before building a posterior on it.
Options from here (a genuine fork)¶
A — Sharp techniques, not coarse firdaria. The theory’s real claim is sect as the marginal of the full event-posterior. Firdaria was a hopeful shortcut; the signal may live in the sharp, angle-tied techniques (directions/transits to the angles, ZR peaks, profected-year lords) that the shortcut skipped. This is bigger (needs the candidate grid + more engines) but is the theoretically grounded path.
B — The sect-dependent dignity/lots channel (spec §5.1 fallback): benefic/ malefic of the sect, the sect light, and the Lot of Fortune/Spirit formula flip. Fuzzier and more temperament-linked (leans on the soft channel we deferred).
C — Reconsider whether events-only can fix sect at all, vs. needing the temperament/chart-coherence signal a human rectifier actually uses.
The machinery (loader, harness, significators, benchmark, contrastive report) is built, tested, and reusable for whichever direction we take.
Phase 1B — malefic-contrary-to-sect probe (option B) — SIGNAL¶
probe_malefic_sect.py. Doctrine: the malefic out of sect is the sharper
destroyer — Mars out of sect by day, Saturn out of sect by night — so a life’s
misfortunes should carry the flavour of its contrary-sect malefic. Prediction:
Mars-flavoured hardship → day, Saturn-flavoured → night. Nearly chart-free
(reads the character of the misfortunes via a priori Mars/Saturn keyword lists),
and a completely different mechanism from firdaria.
metric |
value |
|---|---|
accuracy |
65.1% (41/63) |
decided-only (drop 14 keyword-silent ties) |
65.3% (32/49) |
corr(mars−saturn, day) |
+0.346 — ≈ 2.9 SE from 0, p ≈ 0.005 |
95% CI |
[52.8%, 75.7%] (lower bound just under the 54% majority) |
confusion |
both diagonals dominant (day 22/12, night 10/19) |
Pre-registered gate: still NO-GO (CI-low 52.8% < majority 54%) — but this is a genuine, directionally-correct effect, not the firdaria null. The extremes are convincing: strongest-Saturn lives (Ted Bundy, Hannah Arendt, Ali, Obama) classify night; strongest-Mars (Hemingway, Frida Kahlo, JFK, van Gogh, Plath) classify day.
Interpretation: events do carry sect information — via the malefic-of-sect character of misfortune, not via the firdaria time-lord sequence. Modest (65%), needs development, and the keyword lists carry some researcher DOF (set a priori, but worth a holdout).
Phase 1C — benefic-of-sect mirror + combination — benefic is NULL¶
sect_signals.py, probe_sect_combined.py. Symmetric hypothesis: Jupiter is
benefic of sect by day, Venus by night → Jupiter-flavoured fortune → day,
Venus-flavoured → night.
signal |
accuracy |
corr(score, day) |
|---|---|---|
malefic-only |
65.1% |
+0.346 |
benefic-only |
52.4% |
+0.021 (null) |
combined |
52.4% |
+0.169 (diluted) |
The benefic mirror carries no signal, and combining it dilutes the malefic (+0.35 → +0.17). Diagnosis: fortune-character is domain-linked, not sect-linked — artists accumulate Venus-flavoured fortune (art/exhibitions), scientists and politicians Jupiter-flavoured (awards/office), independent of sect — so the benefic channel injects profession noise. Misfortune-character (sudden/violent vs slow/chronic) is far more universal, which is why the malefic side works and the benefic doesn’t.
Conclusion: keep malefic-only (corr +0.346, p ≈ 0.005) as a real but modest sect prior; drop the benefic. The cheap event-character approach tops out ≈ 65% — useful as one evidence stream, not a decisive classifier.
Where things stand (post-B)¶
Two mechanisms tried from events alone: firdaria timing = null; malefic-of-sect character = real but modest (65%, p≈0.005, doesn’t clear the strict gate); benefic-of-sect = null (domain confound).
Events do carry sect signal, but weakly and only through misfortune character. A decisive sect read likely needs the chart itself (option A: the sharp, angle-tied techniques → full posterior, sect as the marginal), which is the larger build we deferred.
Phase A — time-posterior + the daylight prior — first GO¶
posterior.py, profection.py, sect_classifier.py, run_sect_benchmark.py.
Built the technique-agnostic pipeline (candidate grid → per-candidate likelihood → posterior → sect marginal) and drove it with annual profection (year-lord depends on the rising sign → time-dependent, unlike firdaria). Then the control that reframed everything.
Profection is null (and harmful). Rising-sign recovery is at chance (exact 9.5% vs 8.3%; mean sign-distance 2.95 vs 3.0), and the profection posterior’s sect marginal (65%) is worse than a uniform posterior. Coarse lord-matching carries no time signal — consistent with the firdaria null.
The control that mattered — the daylight prior. A uniform posterior (zero
technique signal) sets p_day = the daylight fraction of the birth day
(longer day ⇒ more likely born by day = P(day | date, lat)). Alone it scores
68.3%, corr +0.40 — beating every event-based signal. The strongest sect
predictor is a free geometric prior that uses no events at all.
But events add real independent value. The malefic-of-sect signal is only mildly correlated with the daylight prior (+0.19), and its partial correlation with sect controlling for daylight is +0.30 — genuinely independent evidence. Combining them (informed prior × event likelihood — the theory’s exact structure) via a 2-feature logistic:
model |
accuracy |
|---|---|
majority baseline |
54.0% |
malefic-alone |
65.1% |
daylight-alone |
68.3% |
daylight + malefic (LOO-CV) |
69.8%, CI [57.6%, 79.8%] |
daylight + malefic (in-sample) |
73.0% |
Pre-registered gate (LOO acc ≥ 65% AND CI-low > majority): GO. Cross-validated, so not overfit; fitted weights daylight +0.80 / malefic +0.72 (both real).
Takeaways:
A calibrated sect classifier at ~70% (LOO) exists — daylight prior + the malefic-of-sect event evidence. First result to clear the bar.
Most of the strength is the free geometric prior; the event evidence adds a real but modest independent boost. This is honest and defensible, not a dramatic rectification win.
Profection (coarse timing) is null — the remaining upside for time (not just sect) is the sharp angle-tied techniques (directions to angles, ZR-from-Fortune peaks), still untested. Those are the real rectification signal if it exists; the pipeline (
posterior.py) is built and ready to host them.
Phase A2 — primary directions (the sharp technique) — null for time¶
directions.py, run_directions_benchmark.py. For each candidate time, direct the
seven planets to the four angles (DirectionsEngine) — hits land at ages that move
strongly with birth time — and score whether directed hits whose promissor
signifies an event fall near that event’s age (de-confounded).
metric |
directions |
chance |
|---|---|---|
time median |Δ| (MAP vs truth) |
406 min |
~360 min |
mean posterior mass ±90 min of truth |
0.138 |
0.125 |
mean posterior mass ±180 min of truth |
0.258 |
0.25 |
sect marginal |
68.3% |
(= daylight leaking through) |
Directions does not localize time — mass-near-truth is at chance and median error is worse than chance. Best-case retest (day-precision events only, tight 0.5-yr orb): median |Δ| 320 min, mass ±90 min 0.132 — still chance. The sect 68% is just the daylight fraction showing through a near-uniform posterior, redundant with the classifier.
Verdict on the timing-technique family (firdaria + profection + directions)¶
All three are null. Automated rectification by “sweep the birth time, match events to timing-technique activations via a significator table” does not carry signal — coarse or sharp. Expert rectification works because a human selects meaningful event↔direction correspondences with judgment; the blind, all-events, significator-table version loses exactly that.
What actually works, and all that works:
the daylight-fraction geometric prior (68%, no events), and
the malefic-of-sect event character (adds independent value → 70% LOO).
Neither is a timing technique. Minute-level time rectification is not achievable with this automated approach; the deliverable is the ~70% sect classifier (to be strengthened by an external birth-hour prior — research pending). This is the central, rigorously-established result of the investigation.
Temperament / personality — null for sect (probe_temperament_sect.py)¶
Tested the soft channel now that full charts are available. Sect-light doctrine: Sun-led (Solar) character → day, Moon-led (Lunar) → night; Solar/Lunar keywords a priori.
value |
|
|---|---|
corr(temperament, sect) |
+0.03 (null) |
corr(temperament, malefic) |
−0.03 (independent, but of noise) |
partial corr(temperament, sect | daylight, malefic) |
+0.11 (n.s. at n=63) |
LOO: daylight+malefic |
69.8% |
LOO: daylight+malefic+temperament |
68.3% (no gain — slightly worse) |
Temperament is null and adds nothing (it slightly hurts LOO). This also settles the chart-contextualised version without building it: “does temperament match the chart’s sect-role assignment” decomposes into the sect light (Solar/Lunar — just tested null) and the benefic of sect (Jovial/Venusian — = the null benefic-events probe). Both building blocks are null.
Why temperament fails where malefic-of-sect works: the malefic signal rides a specific, clean axis — the character of misfortune (violent/Mars vs chronic/Saturn) maps directly onto the out-of-sect-malefic doctrine. General temperament is swamped by the far larger non-sect determinants (Sun sign, Moon sign, dominant planet, Ascendant); the sect overlay is too faint to detect against that. Fittingly, sect shows up in the character of harm, not in general personality — consistent with the tradition emphasising sect most for the malefics’ operation.
Natal dignities / placements — null for sect (probe_dignity_sect.py)¶
Tested planetary sign-dignities two ways: (1) a diurnal-vs-nocturnal dignity balance (new channel), and (2) dignity-weighting the malefic (enrich what works — scale hardship by the natal condition of Mars vs Saturn).
model |
LOO-CV |
|---|---|
daylight + malefic |
69.8% |
daylight + malefic + dignity-balance |
68.3% (worse) |
daylight + malefic(dignity-weighted) |
65.1% (worse) |
Both fail. The dignity-balance’s in-sample partial corr looks sizable (−0.32) but does not survive LOO — textbook noise-as-signal, and a reminder of why every signal is cross-validated. Expected: sect is a horizon fact, ~orthogonal to which signs the planets occupy. Dignity-weighting the malefic degrades it — natal malefic condition is noise for the misfortune-character signal.
Signals tested — the full map¶
channel |
signal |
result |
|---|---|---|
geometry |
daylight fraction (prior) |
+0.40 — works (68%) |
event character |
malefic-of-sect (misfortune flavour) |
+0.35 — works, independent (→70%) |
event character |
benefic-of-sect (fortune flavour) |
null (domain confound) |
timing |
firdaria time-lord × significators |
null |
timing |
annual profection (rising-sign lords) |
null |
timing |
primary directions to angles |
null (sect and time) |
temperament |
sect-light (Solar/Lunar) |
null |
natal dignity |
diurnal/nocturnal balance; dignity-weighted malefic |
null |
Bottom line. Feature space for an automated, corpus-scale rectifier is thoroughly explored. Only daylight prior × malefic-of-sect survives (LOO 69.8%, GO). Minute-level time is null across every timing technique. Further feature-hunting on n=63 has negative expected value (multiple-comparisons risk — the dignity −0.32 that vanished under LOO is the warning).
External birth-hour prior — no improvement (historical cohort) (birth_hours.py)¶
Replaced the uniform-birth-time assumption with an external, cited hourly
distribution (birth_times_research.md; population vital-stats, no chart samples).
Distribution A spontaneous_prewar (nocturnal, peak 04:00) as primary, an
era-aware blend toward the modern daytime curve for later births.
prior (+ malefic) |
LOO-CV |
|---|---|
uniform daylight |
69.8% |
spontaneous_prewar |
66.7% |
era-blend |
68.3% |
corr(prior, sect): uniform 0.398, spontaneous 0.408, era-blend 0.399. The birth-hour prior does not improve sect prediction — equal-or-worse in LOO. Reason: the daylight fraction already captures the date/latitude effect; the hourly curve is broad (peak:trough ~1.9:1) and applied identically to all, so it shifts P(day) ~monotonically (absorbed by the logistic) rather than adding discrimination.
Modern cohort test (resolves the caveat). Added 20 post-1970 AA/A births
(rectification-modern-cohort.yaml) to test the medicalized daytime curve on
the era it’s meant for. It still doesn’t help:
prior |
modern AA (n=17) acc |
corr |
|---|---|---|
uniform daylight |
70.6% |
+0.251 |
modern daytime |
64.7% |
+0.245 |
spontaneous |
47.1% |
+0.245 |
The modern prior shifts every P(day) up ~0.08 (a near-uniform monotonic shift),
so the correlation barely moves (0.245–0.251) — it only slides the 0.5 threshold
and mis-flips borderline night births to day. The lesson: a better prior
(marginal P(day)) is not a better classifier (discrimination). The birth-hour
curve improves calibration of the average but adds no ranking signal; the daylight
fraction already owns the person-to-person variation (date + latitude).
Bonus — out-of-sample validation. These 20 were never in the 63, yet the daylight prior alone scores 70.6% on the 17 AA, matching its ~68% on the historical set. The classifier generalises cleanly across eras. The birth-hour lever is now definitively closed.
Selection-bias / confound check on the malefic signal — robust¶
The corpus is famous + AA-recorded (Western, 19th–20th c., dramatic documented lives). The one positive event signal (malefic-of-sect, +0.35) is the finding most vulnerable to that. Tested the two concrete confounds — profession and sex:
malefic-sect correlation, controlling for |
value |
|---|---|
nothing (raw) |
+0.346 |
gender |
+0.349 (gender explains 0% of sect variance) |
category |
+0.355 |
category + gender |
+0.361 (both explain 5% of sect variance) |
Completely stable (strengthens slightly). Women vs men are day-born at 52% vs 55% — sect is birth time of day, mechanistically independent of who you are, so neither profession nor sex can confound it. The “criminals are violent and happened to be day-born” artifact is ruled out.
What remains (untestable): biographical-emphasis bias (biographers front-page violent events, under-report chronic decline) and whether the signal generalises beyond famous, well-documented lives. These can’t be tested without a non-famous documented-event corpus, which is structurally impossible — validating rectification requires known-time + documented events = famous + AA + Western + recent. That is an inherent ceiling on the whole enterprise, not a fixable flaw. The ~70% classifier is validated on this population, not claimed for humanity.