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DueCare notebooks, datasets, and the reusable kit

A single catalog of the public DueCare surfaces on Kaggle: the analysis and applied notebooks, the open datasets they read, and the importable duecare-llm-kit package. Every analysis notebook is CPU-safe and recomputes its figures live from a public dataset -- no hidden state, attach the dataset and re-run any cell.

How to read the status column

  • live -- published and reachable. It is linked below and from the public hub at duecare-ai.com/data and duecare-ai.com/kernels.
  • queued -- a build script or owner-side draft exists, but there is no verified public URL. Queued is not a publication promise. The item gains a link only after the public page returns successfully and the run/artifacts meet the claim made here.

Slugs follow https://www.kaggle.com/code/taylorsamarel/<slug> for notebooks and https://www.kaggle.com/datasets/taylorsamarel/<slug> for datasets.

Live reconciliation on 2026-07-27 used the authenticated Kaggle command line plus unauthenticated public-page checks. The owner listing contains many legacy and private/unpublished drafts, so owner listing alone is not evidence that a notebook is public. Direct checks confirmed the Prompt Intent and Deterministic Verification notebooks are public and COMPLETE; the active/optional kernel status boundary is maintained in current_kaggle_notebook_state.md.

The same closeout pass validated all three active script-kernel sources, all five active/optional root kernels, generated page-source references, and 31 focused Kaggle/notebook contract tests. Those are offline source and execution- contract checks; they do not relabel canceled Kaggle runs as complete and did not dispatch a new remote run.


Analysis

The harness-lift result, opened up. These read the public grade and text datasets and recompute every figure.

Status Notebook What it is
live Start Here: Harness-Lift Benchmark The benchmark front door: the headline lift and the cross-model board, recomputed live, with a guided tour of the whole collection.
live Does A Safety Harness Help? (flagship) The publication-grade walk-through: thirteen sections, dozens of live charts, the +40.7 headline, and the honest counter-evidence.
live Per-Dimension Grades Explorer The exhaustive one-judge-call-per-dimension sweep: per-dimension A-E lift, sliceable by model and judge.
live Cross-Model Leaderboard Deep-Dive Every model ranked by raw lift and by ceiling-adjusted normalized gain, so a strong baseline is compared fairly with a weak one.
live Prompt And Response NLP Explorer Text analytics over the prompt/response showcase: length, distinctive vocabulary (baseline vs harnessed), refusal and citation markers, readability.
live CoT Reasoning Explorer Browse the chain-of-thought reasoning traces the harness produces, prompt by prompt.
live CoT Reasoning Analysis Quantitative analysis of the reasoning chains: structure, length, and indicator / citation density.
live Harness Grades Data Card Schema, provenance, and coverage of the grades panel, and how to load it. Read this before trusting the charts.
live CoT Reasoning Data Card Schema and provenance of the chain-of-thought dataset.
live Prompt Intent And Attack Explorer The attack taxonomy: intent, framing, and category coverage of the adversarial prompt set.
live CoT Direction And Intent Explorer Where each reasoning chain points: direction, intent, and refusal geometry.
live Corridor And Sector Atlas Lift mapped across migration corridors and labor sectors, so you can see it holds beyond one geography.

Benchmark deep-dives reached from the Start Here index (per-claim analyses over the same grades panel): reproduce the harness lift, where the harness helps most, statistical robustness, plus judge-agreement, methodology-and-controls, benchmark-convergence, impact-and-coverage, and benchmark-as-training-signal (all reachable from the Start Here index above).

Applied use cases

Offline, paste-in workflows. No dataset required; they run as pure local Python around the harness primitives.

Status Notebook What it is
live NGO Case Triage Paste a worker account, get an ILO-grounded triage: indicators, risk level, evidence gaps, next steps, referrals, and a draft note.
live Worker Self-Check A worker pastes a suspicious message and gets a plain-language warning and next steps.
live Platform Moderation At Scale Screen risky recruitment posts and ads into a review queue with a reason for every decision.
queued Chain Of Thought Generator (duecare-chain-of-thought-generator) Turn a prompt into a structured, ILO-grounded reasoning chain.
queued Prosecutor Case Building (duecare-prosecutor-case-building) Draft case-building workflow; present in the owner listing but its public URL returned 404 on 2026-07-27.
queued Regulator Compliance (duecare-regulator-compliance) Compliance-monitoring view for labor ministries and regulators: corridor rules, fee caps, and an evidence trail.
queued Developer Integration (duecare-developer-integration) The software-to-software path: call the harness from your own code, structured request in and structured analysis out.

Advanced

Status Notebook What it is
queued The Entire System (duecare-the-entire-system) End-to-end tour of the whole DueCare substrate: runtime, harness layers, knowledge, training, and judging.
queued Semantic Landscape (duecare-semantic-landscape) An embedding-space map of the prompt and knowledge corpus: clusters, gaps, and coverage.
queued Cross-Industry Capabilities (duecare-cross-industry-capabilities) The same harness across domains beyond trafficking (tax evasion, financial crime, and more).

Knowledge

Status Notebook What it is
queued Knowledge Base Explorer (duecare-knowledge-base-explorer) Browse the GREP rules, the RAG corpus, the ILO instruments, and the corridor fee-caps behind the harness.
queued Getting Started (duecare-getting-started) A one-page hub: set DueCare up in minutes, plus a catalog of every published surface.
queued Fact Check And Reproducibility (duecare-fact-check-and-reproducibility) Verify the headline numbers and reproduce them from the public data.
live Deterministic Verification Offline verification tutorial; anonymous page returned 200 and authenticated status was COMPLETE on 2026-07-27.

Publication queue and stopping decision

No additional notebook needs to be published merely to make the repository look complete. The public catalog already covers the reviewer path, benchmark analysis, applied examples, training-data inspection, and the optional Kaggle Community Benchmark. Bulk-publishing private drafts would add maintenance and link debt without adding evidence.

The queued notebooks remain useful candidates. Advance one only when it closes a named audience or evidence gap, then:

  1. regenerate it from its checked-in builder and run its deterministic/static assertions;
  2. verify every attached dataset version, license, privacy boundary, and claim;
  3. push one notebook deliberately, wait for COMPLETE, inspect the saved outputs, and confirm the public page returns HTTP 200 without credentials;
  4. add its link here and on the website in the same change; and
  5. keep it auxiliary unless root AGENTS.md and kaggle/_INDEX.md explicitly change the three-surface active reviewer path.

Datasets

Open-licensed. Grades and scores carry no response text and no personal data; the text datasets are synthetic composite scenarios with kernel metadata scrubbed and a conservative PII scan applied.

Status Dataset What it is
live Harness Benchmark Grades The judged panel: one 0-100 score per (model, arm, prompt, judge) plus five A-E components. 85,417 grade rows across 7,973 prompts and 8 models. The primary evidence file.
live Harness Per-Dimension Grades Higher resolution: one reasoned judge call per rubric dimension. Re-versioned as the exhaustive sweep grows.
live Cross-Model Harness Leaderboard A citable flat CSV of the cross-model board: baseline, harnessed mean, raw lift, normalized gain, and win rate per model.
live Harness Lift Controls The placebo, negative-control, and applicability-audit results -- including the honest, inconclusive parts.
live Prompt Response Showcase The raw adversarial prompt plus the model's baseline, harness-core, and harness-full answers side by side. 1,087 prompts x 3 responses.
live CoT Reasoning Multi-perspective chain-of-thought reasoning traces grounded in the ILO forced-labour indicators. 2,020 chains, 1,740 train / 280 held out.

Training corpora (measured-response, multiperspective, the proof corpus, and the adapter / byte-model learning studies) are catalogued on the hub's Data & downloads page.

Reproduce the headline in a few lines

Attach the grades dataset to a Kaggle notebook (or download the CSV) and read it with pandas:

import pandas as pd, glob
grades = pd.read_csv(glob.glob("/kaggle/input/**/panel_grades.csv", recursive=True)[0])
piv = grades.groupby(["prompt_id", "arm"])["score_0_100"].mean().unstack()   # mean the judge panel
lift = (piv["harness_core"] - piv["baseline"]).dropna()                       # pair harnessed vs baseline
print(f"mean lift +{lift.mean():.1f} over {len(lift):,} paired prompts, {100 * (lift > 0).mean():.1f}% improved")

These are benchmark response-quality results under an LLM judge panel, not field-detection metrics. Source and build scripts: github.com/TaylorAmarelTech/duecare.

The reusable kit: duecare-llm-kit

The indicator engine, chart helpers, HTML-report generator, corpus exporter, and deterministic verifier that ship embedded in these notebooks -- packaged as importable Python so you can use them without opening a notebook.

No DueCare distribution is published on PyPI yet. From a repository checkout:

python -m pip install -e packages/duecare-llm-kit
from duecare.kit import scan, generate_report

for hit in scan("The agency took my passport and I have not been paid."):
    print(hit["indicator"], "--", hit["ilo_ref"])

generate_report("panel.jsonl", "duecare_report.html")   # self-contained HTML lift report

Full API, CLI, and usage snippets: packages/duecare-llm-kit/README.md.