metadata
language: en
license: mit
task_categories:
- text-classification
tags:
- structural-bottleneck
- stability-geometry
- reasoning
- clarus
- sios
size_categories:
- n<1K
pretty_name: Structural Bottleneck Classification v0.1
What this dataset does
This dataset tests whether a model can detect structural bottlenecks.
The task is simple:
Given a scenario and a structural-bottleneck claim, predict whether the claim is supported.
Core stability idea
A structural bottleneck is a constraint that limits system performance regardless of improvements elsewhere.
Typical bottlenecks include:
- single approval points
- single processing nodes
- unique dependencies
- centralized routing
- irreplaceable personnel
- constrained resources
Removing a bottleneck often increases system capacity more effectively than optimizing surrounding components.
Prediction target
Binary label:
- 1 = a structural bottleneck is present
- 0 = a structural bottleneck is not present
Row structure
Each row contains:
- scenario_id
- scenario_text
- claim
- label
Files
- data/train.csv
- data/test.csv
- scorer.py
- README.md
Evaluation
python scorer.py --predictions predictions.csv --truth data/test.csv
Structural Note
This dataset is intentionally small.
Its purpose is to test whether a model can identify limiting constraints embedded in system structure rather than transient operational issues.
License
MIT