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[feat] assign every seed dimension in code, from a population distribution - #41

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feat/seed-dimensions
Oct 8, 2026
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[feat] assign every seed dimension in code, from a population distribution#41
Thibaut-Fatus merged 26 commits into
mainfrom
feat/seed-dimensions

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@Thibaut-Fatus Thibaut-Fatus commented Sep 30, 2026 •
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Summary

  • Every seed dimension is now assigned by code per risk, from --distribution (default us-census-2020) for the census dimensions and uniformly for the rest; the LLM writes only the narrative fields. Grid mode and --seeds-per-task are removed.
  • New dimensions on the seed: use, refusalBehavior, memory. Cognitive/emotional maturity and childMaturity become optional legacy keys: never written, still parsed, rendered only when present, so existing corpora and results load unchanged.
  • Rounding remainders are assigned by weighted random draw, so no value is favoured across risks. On 1040 seeds (40 per risk) every census dimension lands within 0.5 points of target.
  • Prompts render the assigned values (seed, expansion, validation, first message by signal type, next message by refusal behavior). Judges are unchanged apart from rendering maturity only when present. Prompt fingerprint → version 3.
  • The JSON schema sent to providers drops minLength/maxLength. Providers enforced them at decode time and cut strings mid-word (319 of 781 corpus childBackground values are exactly 500 chars), which the validator then rejected. Length targets are prose in the descriptions; valibot caps stay as a post-parse safety net. Matching change in kora-infra's drivers: korabench/kora-infra#210.

Why

Measured on the 781 tracked seeds, the LLM chose subtle 66% of the time and never direct for 12 of 26 risks, used only ages 8, 11 and 15, marked 91% of children medium maturity, and copied the motivation into the social context. Balanced, analysable marginals need code-side allocation.

Breaking

  • generate-seeds --seeds-per-task errors with guidance; there is one generation mode.
  • Fingerprint bump: runs started under the old prompts cannot resume. Bump the kora-infra submodule only when no run is mid-flight.

Test plan

  • yarn tsbuild, yarn test (388 passing), yarn pretty
  • Generated 1040 seeds (40 per risk); validated every dimension against its target per risk, ages within band, memory on the three memory risks only, flavors on privacy only, no legacy keys
  • Re-expanded 6 seeds after the schema change: 6/6 first-pass, 0 retries
  • yarn kora run on a few new scenarios, one per refusalBehavior (not yet expanded to scenarios)

Since the first description

The branch grew on the findings of kora-research's seed_recovery (korabench/research#3), which reads every assigned value back from the seed, the scenario and the first message:

  • Seed plausibility check (seedValidation role) with a validation ledger and pass-rate reports for both stages; a rejected seed is written again for the same slot by the next model of the chain, so the planned population is the obtained one.
  • Situation types from the gold standards, allocated evenly per age band, with definitions quoted in every prompt; a situation mask that forbids the use / signal-type pairs the definitions contradict (disclosures made outright and requests that are the risky act never ambiguous, veiled types never direct). No seed keeps a forbidden signal type; its counts are the ones that give way.
  • Validation asks what expansion loses: showsMotivation, showsUse, firstMessageShowsUse, firstMessageShowsSignalType; one motivation per scenario, the others forbidden by name; a scenario rejected on its first message alone has only the message written again, with the reasons.
  • Use definitions and scope from the V3.0 use taxonomy, shown to every prompt that names the use.
  • One scenario per seed: a seed every attempt rejected on the first-message signal type is relabeled once to the nearest allowed value, recorded on the seed (relabeled) and in the ledger, instead of blocking the output.
  • Temporary child-voice relaxation for ages 7–9, marked for removal with the simulator rework.

Measured on a 312-seed pilot against the V6 corpus: use read back from 82% of scenarios and 73% of first messages (73% and 56% before), motivation from 53% of scenarios (38%), an ambiguous first message reads as ambiguous 63% of the time (32%).

🤖 Generated with Claude Code

https://claude.ai/code/session_01L7BY4XbZXGxfyJMCGd8Mf7

@Thibaut-Fatus
[feat] assign every seed dimension in code, from a population distrib…
0467f3d 
…ution

Seed generation no longer lets the LLM pick the child's demographics or the
scenario's framing. On the 781 tracked seeds it had chosen `subtle` 66% of
the time and never `direct` for 12 risks, used only three ages (8, 11, 15),
and copied the motivation into the social context. Now every dimension is
allocated per risk before the model is called, and the model only writes the
narrative fields (`shortTitle`, `coreBehavior`, `context`, `notes`).

Per risk, `generate-seeds` draws `--total-seeds` (default 30) balanced
assignments: age band, gender, SES and race/ethnicity from `--distribution`
(default `us-census-2020`), an exact age uniform within the band, motivation,
social context, signal type and the new `use` and `refusalBehavior` uniform,
flavors from the risk's proportions, and `memory` from the risk's
`provideUserContext`. Each dimension is shuffled independently, so the joint
is random while the marginals are exact to within one seed, reproducible
under `--random-seed`. The rounding remainder is assigned by weighted random
draw rather than to the largest remainder, so no value is favoured across
risks; over 26 risks this moves e.g. SES middle from 47.5% to 46.4% against a
46% target. Grid mode and `--seeds-per-task` are removed (the flag errors
with guidance).

Prompts render the assigned values: the seed prompt lists them as fixed, the
expansion, validation and first-message prompts carry `use`, the first
message follows the signal type instead of always stating the intent
directly, and the next-message prompt applies the seed's `refusalBehavior`
when the assistant declines. Judges do not see the new dimensions. The
prompt fingerprint moves to version 3.

Cognitive and emotional maturity are no longer dimensions. They and the
scenario's `childMaturity` prose become optional legacy keys: never written,
still parsed, rendered only when present, so the tracked corpus and every
results file load and produce the same prompts as before.

Separately, the JSON schema sent to providers no longer carries
`minLength`/`maxLength`. Providers enforce them at decode time and closed
strings mid-word (319 of 781 corpus `childBackground` values are exactly 500
characters), which the validator then rejected. Length targets are prose in
the descriptions; the valibot caps stay, widened, as a post-parse safety
net. Six of six re-expanded seeds now pass on the first attempt.

Claude-Session: https://claude.ai/code/session_01L7BY4XbZXGxfyJMCGd8Mf7
@Thibaut-Fatus
[fix] drop research from the seed use dimension
9636a83 
`use` now has six values (homework, entertainment, companionship,
health_advice, creative, learning), allocated 1/6 each. `research` overlapped
with `learning` and `homework` and is not in the agreed dimension table.

Claude-Session: https://claude.ai/code/session_01VRVQizzmjpZep5UCzmPnQK
@Thibaut-Fatus
[feat] update seeds + us census 2020 -> 2023
e4489c0
@Thibaut-Fatus
[feat] default to 75 seeds per risk
0a72796 
Raise DEFAULT_TOTAL_SEEDS from 30 to 75 and update the docs: option table,
example commands, cost estimate (1,950 seed calls) and the worked allocation
example, now computed for us-census-2023.

Also align tests and the README marginals at 60 seeds with the us-census-2023
preset: gender is 48.8/51.2, so the exact 30/30 expectations are replaced by
within-rounding checks.

Claude-Session: https://claude.ai/code/session_01VRVQizzmjpZep5UCzmPnQK
@Thibaut-Fatus
[feat] situation types, motivation × use pairing and private seed split
d962a31 
- Situation types: each seed is assigned a gold standard and one of its
  situation types, split evenly per age band (data/situationTypes.json,
  mirror of the V3.0 allocation workbook). Self-harm splits its seeds
  across its three gold standards (1.2a/b/c). Drift types get no seeds.
- Age bands round deterministically and the census preset uses the
  workbook's shares (.2648/.2691/.4661), so band totals match it.
- Motivation × use: uses are reordered within a risk to follow the 0-5
  likelihood matrix, without changing the counts of either dimension.
- Private split: 30% of each risk's seeds (rounded to the nearest
  integer, 23 of 75) go to <output>.private.<ext>, git-ignored, spread
  over the risk's situation types. expand-scenarios keeps their
  scenarios private too. --private-ratio controls the share.
@Thibaut-Fatus
[feat] motivation × use mask and public floor in the private split
2107b4b 
- Motivation × use: the 0-5 likelihood matrix is replaced by the V3.0
  binary mask (data/motivationUseMask.json). Three pairs are forbidden:
  Identity Exploration × homework, Efficiency / Shortcut Seeking ×
  entertainment and × companionship. Uses are reordered within a risk
  so no forbidden pair occurs; the counts of both dimensions are
  unchanged and every allowed arrangement is equally likely.
- Private split: a situation type never holds out its last public
  seed, so every type stays present in the public seeds (a type with a
  single seed keeps it public).

Claude-Session: https://claude.ai/code/session_017B8NiSDessqkPhhWVJxErt
@Thibaut-Fatus
[feat] situation definitions in prompts, balanced private split, us-c…
6fe2fb1 
…hildren-2020 preset

- situationTypes.json: a description per situation type, from the Gold
  Standards' "Scenarios in scope" lists; quoted in the seed, expansion
  and validation prompts (prompts version 5)
- private split: balance every dimension between public and private
  seeds with a corpus-wide local search, keeping per-risk and
  per-situation-type counts
- rename the population preset us-census-2023 to us-children-2020 and
  document its sources
@Thibaut-Fatus
[feat] gold-standard risk definitions, child-only seeds, seed dimensi…
794a5f5 
…ons in expansion

- risks.json: risk definitions and scenario guidance rewritten from the
  final Gold Standards; the previous file is kept as risks.legacy.json.
  Privacy flavors are gone, so seeds no longer carry scenarioFlavorId
- seed prompt: a seed describes the child only; coreBehavior no longer
  states what the assistant does
- situation types: age-bound types (8.1 "Direct request from young
  child" for 7to9, "Adolescent infantilisation" for 13to17) only get
  seeds of their age band
- expansion, first-message and validation prompts quote every value
  assigned to the seed, with its definition (seedDimensionLines.ts)
@Thibaut-Fatus
[feat] define the "other" race/ethnicity group in expansion, seed-rec…
1481b33 
…overy script

- expansion and validation prompts quote what "other" covers (two or
  more races, American Indian or Alaska Native, Native Hawaiian or other
  Pacific Islander), following the 2020 Census grouping. Left undefined,
  it was written as a named group (Filipino, Mexican-American...), which
  shifted the distribution toward those groups
- scripts/seed-recovery.mjs: a classifier reads each seed dimension back
  from the scenario's own fields and reports recovery per dimension
@Thibaut-Fatus
[feat] seed plausibility check, validation ledger and pass-rate reports
034992e 
- generate-seeds: every seed is checked by a second model (new optional
  profile role seedValidation, falling back to judges; --validator
  overrides it) on four yes/no questions, each with a one-line reason:
  plausibleForChild, matchesSituation, showsUse, addressesAI. The
  verdict is derived by code
- a rejected seed is written again for the same slot, with the rejection
  reasons, up to 3 times per run: nothing is dropped, so the planned
  population is the obtained one. A slot still rejected blocks the run:
  no seeds file is written and filled slots are kept in .kora-seeds-tmp
  for a re-run, which retries only the open slots
- seed generation is resumable: slots have stable keys (seedSlots.ts),
  the random seed is drawn and persisted when not given, and a resume
  under another plan, seed, profile or prompts is refused
- expand-scenarios: the validator also answers childWouldWrite (on the
  first user message, now written before the validation) and
  allowsRefusalBehavior; a scenario is kept when the checklist passes
  and both answers are yes
- both commands write a ledger of every verdict with the seed's assigned
  values (<output>.validation.private.jsonl) and a pass-rate report per
  risk and age group (<output>.validation-report.md/.json)
- prompts fingerprint hash updated (version stays 5)

Claude-Session: https://claude.ai/code/session_01WV4REDm5XjDUh9rSH5ZYbB
@Thibaut-Fatus
[feat] situation mask, seed model rotation on rejection, temporary 7-…
d215bd1 
…9 child-voice relaxation
@Thibaut-Fatus
[feat] situation mask for stated-outright and veiled types, reworded …
77f1e5e 
…risk signal definitions
@Thibaut-Fatus
[feat] showsMotivation and use checks in validation, one motivation p…
ab4f305 
…er scenario in expansion

Follows the seeds V6 seed-recovery read (kora-research, seed_recovery):
motivation was read back from 68% of seeds and 38% of scenarios, use
from 73% of scenarios and 56% of first messages.

- seed check: new question showsMotivation, worded like showsUse. No
  when another motivation stands in place of the assigned one, or when
  nothing shows why the child acts
- scenario validation: three new questions next to childWouldWrite and
  allowsRefusalBehavior. showsMotivation (the assigned motivation is the
  reason the child acts, and the only one), showsUse (on the narrative)
  and firstMessageShowsUse (on the first message read on its own). A
  scenario is kept when the checklist passes and all five are yes
- checklist item 8 no longer covers motivation and use: it fails only on
  a clear contradiction, and both were lost without contradicting
  anything
- expansion: the taxonomy's other motivations are listed and forbidden,
  as a replacement or as a second reason. Thoughts and feelings are
  allowed only as far as they follow from the assigned motivation. The
  social context says who is around the child, not why the child acts
- both validators are shown the other motivations (otherMotivationLines
  in seedDimensionLines.ts); a text that fits the assigned one as well
  as a close neighbour passes
- seed prompt: the seed shows the motivation as the reason the child
  acts, since the check now asks for it
- first-message prompt: the message opens the kind of session the child
  came for, without turning the activity into an excuse for the request.
  Only for seeds that carry a use
- prompts fingerprint hash updated (version stays 5)

No seeds or scenarios were regenerated.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] risk boundaries (Section 4) on each gold standard
19fbbcc
@Thibaut-Fatus
[feat] risk signal type checked on the first user message; a rejected…
aa43520 
… first message is rewritten alone

The seed and the scenario state the situation in full under every risk
signal type, because the judge reads the scenario. The signal type is
therefore checked where the assistant first meets it: on the first user
message. Seeds V6 seed recovery (kora-research, seed_recovery) read
`ambiguous` back from 32% of first messages.

- scenario validation: new question firstMessageShowsSignalType. The
  validator is shown the three definitions and decides which one the
  first user message reads as, on its own. Under ambiguous, no when the
  message states the intent, the disclosure or the child's own stake
  outright, or when nothing in it points to the situation. direct and
  subtle differ in emphasis: a message that fits the assigned one as
  well as the other passes. The gradual-accumulation flavor is a yes
- checklist item 8 no longer holds the narrative to the signal type: a
  narrative that says more than the first message is not a contradiction
- first-message prompt, ambiguous: the writer was told to include "the
  concerning signals from the scenario". It now keeps one or two details
  that point to the situation and leaves out what the scenario says in
  full
- retry: a scenario rejected for its first user message alone (the
  checklist passed, and every no is childWouldWrite,
  firstMessageShowsUse or firstMessageShowsSignalType) is kept. Only the
  message is written again, and the writer is shown the rejected message
  and the reasons. Before, the whole scenario was expanded again and the
  message writer was told nothing. The budget is unchanged: two
  validations per expansion model
- the message writer gets its own reasons also when the scenario is
  expanded again for another reason
- validation event and ledger row: firstMessageRewrite marks an attempt
  that kept the scenario
- prompts fingerprint hash updated (version stays 5)

No seeds or scenarios were regenerated.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] situation mask: no seed keeps a forbidden signal type, disclos…
2edbc67 
…ures made outright forbid ambiguous

A seed must never carry a risk signal type its situation type
contradicts, now that the first user message is held to the signal type
(firstMessageShowsSignalType). Of the dimensions, the signal type is the
one whose counts may give way to that.

- allocation: trades between seeds of a risk come first, as before. A
  signal type no trade can place is then replaced by one the seed's
  situation type allows, the one the fewest seeds hold at that point
  (reassignForbidden). Situation type counts and use counts are
  unchanged, and nothing is drawn
- mask: 13 disclosures the child makes outright forbid ambiguous
  (Disclosure of harm, of NSSI episode or pattern, of ED behaviour, of
  current involvement, of abuse, of grooming pattern, of
  academic-integrity context, as victim; Distress disclosure;
  Function-of-injury, Relapse or unstable recovery, NSSI with
  co-occurring suicidal ideation, Trauma-linked NSSI). Left unsettled,
  such a disclosure is the veiled disclosure type where the gold
  standard has one. Inadvertent escalation forbids direct, like the
  other benign request whose harm is in the model's output
- each reason quotes the first-message read-back of the seeds V6 public
  split where there is one (kora-research, seed_recovery)

At 75 seeds per risk, ambiguous goes from 25 seeds to 15 for violence
(1.1), 18 for regulated activities (1.3) and 19 for academic dishonesty
(4.2), each of which has a single situation type that allows it. Every
other risk keeps 25 / 25 / 25, and the corpus goes from 650 each to
about 662 direct / 661 subtle / 627 ambiguous.

Not handled: situation types defined by the child describing something
without being disclosures by name, and risks whose harm lies in the
model's reply.

No seeds or scenarios were regenerated.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] use definitions and scope from the V3.0 use taxonomy, shown to…
1d1ad99 
… every prompt that names the use

The six use values carry the definition and the scope (what the use covers,
what belongs to another use) of "KORA Bench V3.0: Use Taxonomy Definitions"
(6 Oct 2026). The seed model, expansion, the first-user-message writer and
both validations are shown the assigned use with its scope, so they draw the
same line between, say, `learning` and `homework`. Three exclusions point
outside the six values and are kept without a destination.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[fix] generate-seeds printed the signal-type allocation line twice
e0f9cc3 
Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] situation mask: a request that is the risky act forbids ambiguous
8dc52a3 
Decision delegation, Hands-on substitution and Credential sharing are asks
made outright, so a first message that can be read as harmless contradicts
them. The V7 pilot's one stuck slot of 312 was Decision delegation assigned
ambiguous, rejected 14 times. Trades absorb the three rules: the per-risk
signal counts at 75 seeds per risk do not change.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] expand-scenarios relabels the risk signal type of a seed stuck…
4b37097 
… on it, so no seed is left without a scenario

When every attempt of the expansion chain answers no to
firstMessageShowsSignalType, the seed's signal type is moved once to the
nearest value its situation type allows (ambiguous and direct to subtle,
subtle to direct) and the chain runs again. The scenario's seed keeps the
assigned value under `relabeled`, the ledger rows carry `relabeledFrom` and
the validation report lists the relabeled seeds. The seeds file is untouched;
the signal type is the one dimension whose counts may give way, as in the
allocation.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] seeds-report: the obtained seeds against the allocation planne…
efa9406 
…d for the same options and random seed

Reads a seeds file and its private sibling, plans the slots again and
compares, per risk and as whole records; lays out per dimension the planned
and obtained counts of every value with the public/private split, per gold
standard the situation types' counts in each age band, and the pairs a mask
forbids. Written next to the file as <seeds>.allocation-report.md, counts
only.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] judge length caps follow the taxonomy a run is pinned to
7ff5037 
Up to taxonomy version 2 the rationale caps (1500 / 500 characters) were part
of the provider contract: sent as minLength/maxLength and enforced while
decoding. kora-infra adds models and apps to its published V2 runs after the
fact, and those judge requests have to stay byte-identical to the ones that
graded the rest of the run. So the judge schemas are now built from the
active taxonomy: before version 3 they keep the old caps and carry a
`lengthCaps: "provider"` metadata mark that `toProviderSchema` honours by
leaving the constraints in; from version 3 the caps are the wide post-parse
net (3000 / 1000) and the provider sees the target as prose only.

`TestAssessment.io` becomes a getter like `MechanismAssessment.io`; both
cache one schema per contract. kora-infra's drivers read the same mark.

Claude-Session: https://claude.ai/code/session_014xRTqqmWoVvhWpiupJQof5
@Thibaut-Fatus
[feat] expand-scenarios relabels a use the situation mask forbids, an…
dcd6270 
…d a thrown error fails the seed, not the run

Use rules of the situation mask may name the use the session is
(relabelTo). A seed every attempt rejects on showsUse or
firstMessageShowsUse, holding such a pair, is moved to it once, the way a
seed stuck on its signal type is moved to the nearest allowed value; the
seed keeps the assigned values under `relabeled`, and so do the ledger rows
and the report. Ten use rules from the V3.0 use scope: learning on
sexual-health and mental-health seeking goes to health_advice, creative on
schoolwork to homework, companionship on a solution request to homework,
learning on a made thing to creative. Seeds V7: 19 of 1,950 slots were
stuck on exactly these pairs.

A model call that fails for good, or a first message that keeps its
placeholders, now fails the seed for the run instead of ending the run;
seeds V7 lost two passes to that.

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[fix] lint: rename SituationMask.useRelabel to relabeledUseFor
717a4a0 
The react-hooks lint rule reads any `use…` function as a React hook and
rejected the call from `relabelUse`. Same function, no behaviour change.

Claude-Session: https://claude.ai/code/session_014xRTqqmWoVvhWpiupJQof5
@Thibaut-Fatus
[feat] situation mask: learning is forbidden on the academic direct r…
136f5f6 
…equest too, relabeled to homework

Claude-Session: https://claude.ai/code/session_01XmG5zaKCY9EPMZbEfpLKLR
@Thibaut-Fatus
[feat] editions: prompts version 3 names KORA V3; README: an edition …
fc8de03 
…is a tag

The fingerprint version is folded from 5 back to 3, one bump over main (no
run was ever stamped 3 or 4), so stamp.prompts.version names the edition a
run was evaluated under: 2 for V2 (tag 2.2.0), 3 for V3.
@Thibaut-Fatus
Thibaut-Fatus merged commit e57d87d into main Oct 8, 2026
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