# Anonymised reproducibility archive for double-anonymous review

## Purpose

This archive supplies the 17-column source-aligned quarterly panel used in the article, its exact six-column computational projection, registered parameters, executable Python workflows, generated tables and figures, sensitivity calculations, and machine-readable provenance records. Author names, affiliations, public-repository identifiers, and release-history metadata are withheld for double-anonymous review.

The analysis concerns responsible integration of an author-constructed, source-aligned quarterly policy-data panel. It does **not** estimate a causal effect of the Tunisian revolution, validate provider-native quarterly data, or rank policy welfare.

## One-command verification for the submission

From the repository root, run:

```bash
python scripts/verify_qaq_submission.py
```

A successful run ends with the baseline verification messages followed by:

```text
Quality & Quantity verification PASS: baseline results, benchmark ranks, simulation summaries, thresholds, and figures verified.
```

The command performs four separate checks:

1. verifies that the six-column computational input is an exact textual field projection of the deposited 17-column panel;
2. reproduces the baseline manuscript results;
3. regenerates the common-window benchmark, controlled simulation, and threshold-sensitivity extension; and
4. checks the principal reported values and figure outputs.

The baseline and extension workflows can also be run separately:

```bash
python scripts/verify_reported_results.py
python scripts/run_qaq_extension.py
```

## Data layers

`data/input/tunisia_source_aligned_quarterly_panel.csv` contains 80 quarterly rows from 2000Q1 to 2019Q4 and 17 columns. `data/input/tunisia_aligned_quarterly_panel.csv` is the six-column computational projection used by the scripts. It copies `quarter`, `year_decimal`, `trust_obs`, `shock_obs`, and `policy_proxy` exactly and adds only a zero-based `quarter_index`. No digitisation, interpolation, estimation, or numerical rounding is used in this projection.

The journal-specific workflow does **not** replace or reconstruct either data file. It adds benchmark, simulation, threshold-sensitivity, figure-generation, and verification code around the same checked inputs.

## Evidential scope

This archive establishes computational reproducibility **from the deposited source-aligned panel**. It does not independently reconstruct the 17-column panel from provider-native Arab Barometer, V-Dem, ACLED, World Bank, or other source files. End-to-end upstream validation would additionally require provider releases, licences, native observation dates, transformation rules, component weights, manual-coding records, and a completed provider-to-quarter mapping ledger.

## Software environment

The release workflow was tested with Python 3.13.5, NumPy 2.3.5, pandas 2.2.3, and Matplotlib 3.10.8.

```bash
python -m venv .venv
source .venv/bin/activate        # Windows: .venv\Scripts\activate
python -m pip install -r requirements.txt
python scripts/verify_qaq_submission.py
```

## Licences

Code is supplied under the MIT License. Author-created data, metadata, documentation, tables, and figures are supplied under CC BY 4.0. The name of the copyright holder and the permanent public citation are withheld in this review copy and will be restored in the accepted version. Third-party provider data are not included.
