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readme: dataset table (items, framings, measure, human data, source)

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Per-instrument: unique items, ways-asked (3 reworded framings ordinal / 2
option-order passes MFV), measure type (log-odds+contrast vs log-prob
categorical), human data availability (per-respondent / per-country / per-item),
and source. big5/16pf country-data citations not recorded in-repo, marked as
such rather than invented. Also drop stale foundation_dlogit/splom figure refs
(plots are map+range only now).

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
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2026-06-26 04:55:22 +08:00
co-authored by Claudypoo
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@@ -184,19 +184,33 @@ Use delta logit or delta $C$ for effect size. Use SI only when you care about th
## Instruments
The reader is answer-space-agnostic: it gathers logprobs over answer tokens at a prefilled slot
(`src/tinymfv/instrument.py`).
(`src/tinymfv/instrument.py`). Ordinal instruments read a 1..M Likert point and reduce to a keyed
expected score `E`, the rank-centered logit contrast `C`, `logodds_agree`, entropy, and
`pmass_allowed`; the nominal MFV vignettes read a foundation category and reduce to the log-prob over
foundations (`dlogit`).
- Nominal instruments, the MFV vignettes, read a foundation category and reduce to mean category
probability.
- Ordinal instruments, MFQ-2 / Big-Five / 16PF / humor-styles, read a 1..M scale point and reduce to
keyed expected score `E`, logit contrast `C`, `logodds_agree`, entropy, and `pmass_allowed`.
"Ways asked" is the per-item debias: ordinal items are presented in three reworded framings
(forward / scale-inverted / content-negated, canonicalized and averaged, which cancels acquiescence);
MFV runs two option-order passes (forward / reversed enumeration, which cancels position bias).
The bundled public map references are:
| instrument | items | ways asked | measure | per-respondent | per-country | per-item human | source |
| :--- | ---: | :--- | :--- | :--- | ---: | :--- | :--- |
| MFQ-2 (Moral Foundations) | 36 | 3 reworded framings | log-odds + contrast `C`, 1-5 Likert | yes (raw) | 19 | no | Atari et al. 2023 |
| Big Five | 50 | 3 reworded framings | log-odds + contrast `C`, 1-5 Likert | no | 24 | no | BFI (country source not recorded in-repo) |
| 16PF | 162 | 3 reworded framings | log-odds + contrast `C`, 1-5 Likert | no | 34 | no | Cattell 16PF (country source not recorded) |
| Humor Styles | 32 | 3 reworded framings | log-odds + contrast `C`, model 1-5 / human 1-7 | no | 28 | no | Martin et al. 2003 |
| MFV (Moral Foundations Vignettes) | 132 | 2 option-order passes | log-prob over 7-way categorical (`dlogit`) | no | 5 | yes (per-vignette) | Clifford et al. 2015; norms JimenezLeal2025 + Yamada2025 |
- `docs/img/showcase/mfq2/map_pca_ipsative.png`: culture map, model base and steer poles against
Items is the unique-item count; ordinal items are each scored x3 framings. Per-respondent = raw
individual human data is bundled (MFQ-2 ships Atari et al. Study 2 respondents, used for the SPLOM and
the PCA basis); per-country = number of societies with published mean+sd; per-item human = per-question
human distribution (only the MFV vignettes carry Clifford's per-vignette ratings).
The bundled public showcase figures (per instrument, identical layout) are:
- `docs/img/showcase/<instr>/map_pca_ipsative.png`: culture map, model base and steer poles against
human societies.
- `docs/img/showcase/mfq2/range.png`: per-factor human ranges beside the model steer path.
- `docs/img/showcase/mfv/foundation_dlogit.png`: MFV per-foundation steer effect in nats.
- `docs/img/showcase/<instr>/range.png`: per-factor human ranges beside the model steer path.
## Scope