Datasets:

od2961
/

inductive-forecasting-data

pretty_name: Inductive Forecasting Study — Anonymous Data Release
language:
  - en
license: other
task_categories:
  - text-generation
  - reinforcement-learning
tags:
  - forecasting
  - reasoning
  - prediction-markets
  - synthetic-data
  - behavioral-evaluation
configs:
  - config_name: exp1_updates
    data_files:
      - split: test
        path: data/exp1/updates.parquet
  - config_name: exp1_review_materials
    data_files:
      - split: test
        path: data/exp1/review_materials.parquet
  - config_name: exp2_coin_city_tasks
    data_files:
      - split: test
        path: data/exp2/tasks.parquet
  - config_name: exp2_coin_city_responses
    data_files:
      - split: test
        path: data/exp2/responses.parquet
  - config_name: exp3_coin_city_transfer
    data_files:
      - split: train_causal
        path: data/exp3_coin_city/train_causal.parquet
      - split: train_population_prior
        path: data/exp3_coin_city/train_population_prior.parquet
      - split: train_structureless
        path: data/exp3_coin_city/train_structureless.parquet
      - split: test
        path: data/exp3_coin_city/test.parquet
  - config_name: exp3_coin_city_scores
    data_files:
      - split: test
        path: data/exp3_coin_city/scores.parquet
  - config_name: exp4_historical_markets
    data_files:
      - split: train
        path: data/exp4/train.parquet
      - split: validation
        path: data/exp4/validation.parquet
      - split: test
        path: data/exp4/test.parquet
  - config_name: exp4_locked_test_outputs
    data_files:
      - split: test
        path: data/exp4/locked_test_outputs.parquet
  - config_name: exp4_evidence_updates
    data_files:
      - split: test
        path: data/exp4/evidence_updates.parquet
  - config_name: appendix_domain_transfer
    data_files:
      - split: train_d1
        path: data/appendix_domain/train_d1.parquet
      - split: train_d2
        path: data/appendix_domain/train_d2.parquet
      - split: train_d3
        path: data/appendix_domain/train_d3.parquet
      - split: train_structureless
        path: data/appendix_domain/train_structureless.parquet
      - split: test
        path: data/appendix_domain/test.parquet
  - config_name: appendix_dag_transfer
    data_files:
      - split: train_family
        path: data/appendix_dag/train_family.parquet
      - split: train_population_prior
        path: data/appendix_dag/train_population_prior.parquet
      - split: train_structureless
        path: data/appendix_dag/train_structureless.parquet
      - split: test_family
        path: data/appendix_dag/test_family.parquet
      - split: test_population_prior
        path: data/appendix_dag/test_population_prior.parquet
  - config_name: appendix_dag_zero_shot
    data_files:
      - split: test
        path: data/appendix_dag/zero_shot_scores.parquet
  - config_name: appendix_mechanism_transfer
    data_files:
      - split: train
        path: data/appendix_mechanism/train_*.parquet
      - split: test
        path: data/appendix_mechanism/test_*.parquet
  - config_name: appendix_mechanism_scores
    data_files:
      - split: test
        path: data/appendix_mechanism/scores.parquet

Inductive Forecasting Study — Anonymous Data Release

This repository is the anonymous data companion to a paper studying behavioral signatures of inductive reasoning in language-model forecasts. It packages the frozen inputs, model responses, row-level scores, and aggregate result artifacts used by the paper's four main experiments, together with synthetic appendix transfer studies.

The release is organized as Hugging Face dataset configurations so each study can be loaded independently:

from datasets import load_dataset

updates = load_dataset("od2961/inductive-forecasting-data", "exp1_updates")
coin_city = load_dataset(
    "od2961/inductive-forecasting-data",
    "exp2_coin_city_responses",
)
historical = load_dataset(
    "od2961/inductive-forecasting-data",
    "exp4_historical_markets",
)

Experiment 1: selective updating

exp1_updates contains one row per frozen model × market × evidence packet × run record from the June 17 numerical authority. It includes initial and updated probabilities, evidence direction, EHC/HFC/ICS indicators, and parsing status. The source report and threshold analysis are under artifacts/exp1/.

exp1_review_materials contains the 18 blinded fictional reports shown in the human materials review. Individual participant ratings and timestamps are not released because participation consent did not explicitly establish consent for public row-level redistribution. Aggregate review results remain available under artifacts/exp1/.

Experiment 2: Coin City

exp2_coin_city_tasks contains the frozen target-only, no-context, correct-context, misleading-context, and arbitrary-symbol prompts joined to their answer key. exp2_coin_city_responses contains all production model responses, including the matched arbitrary-symbol control set, joined to the same task and gold fields. Failed pilots and corrupt pre-repair files are excluded.

Experiment 3: trained Coin City transfer

exp3_coin_city_transfer contains the 4,800-row causal, population-prior, and structureless training sets plus the common 1,440-row held-out evaluation set. exp3_coin_city_scores contains the registered greedy and five-draw Qwen3-4B endpoint score rows for the base, causal, population-prior, and structureless conditions. Checkpoints are not part of this dataset repository.

Experiment 4: historical-market transfer

exp4_historical_markets contains the checksum-locked 1,736/512/1,024 train/development/test tasks derived from a public Polymarket archive. exp4_locked_test_outputs contains base and three-seed final forecasts. exp4_evidence_updates contains the secondary paired evidence-update outputs. The 21 GB upstream scrape is not redistributed.

Appendix studies

The remaining configurations contain the registered Coin-* domain ladder, DAG family, and mechanism-composition train/evaluation datasets. Final score ledgers are included when the paper's frozen analysis manifest names an exact ledger.

Provenance and construction

Real-market questions and historical prices were collected from Polymarket's public interfaces. The derived task rows preserve the study's point-in-time filtering and family-disjoint split.
Coin City, Coin-*, DAG, and mechanism-family tasks are synthetic and generated by the study code.
Model response rows are machine-generated outputs from the deployments named in each record or accompanying artifact.
release_manifest.json records row counts and explicit exclusions.
SHA256SUMS authenticates every published file.

Absolute cluster paths and author-identifying endpoint names are not included. Authentication secrets were never intentionally written to the source records; the release builder also performs a fail-closed secret and identity scan.

Limitations and responsible use

The synthetic studies are behavioral benchmarks, not demonstrations of a particular internal representation. The historical-market tasks inherit selection biases and limitations of prediction-market archives. Static question/rules text cannot always be proven point-in-time, as described in the paper. Model outputs may contain errors or unsupported claims and should not be treated as factual or as financial advice.

Some Experiment 1 records contain fictional, explicitly labeled evidence packets about real people and events. Preserve the fictional notice when displaying or redistributing these materials.

Licensing

See LICENSE.md. The repository uses license: other because it combines original synthetic benchmarks with third-party market-derived fields and model outputs that are subject to their respective source/provider terms. No blanket relicensing of third-party material is asserted.

Citation

During double-blind review, cite this repository as:

Anonymous Authors (2026). Inductive Forecasting Study — Anonymous Data Release. Hugging Face Datasets.

The card and citation should be updated after deanonymization.