README.md

metadata

title: JuaKazi Gender Sensitization Engine
emoji: ⚖️
colorFrom: red
colorTo: green
sdk: docker
app_port: 7860
pinned: false

JuaKazi Gender Sensitization Engine

A multilingual gender bias detection and correction system for African language text, built for the AI BRIDGE programme.

What it does

Detects and rewrites gender-biased language in Swahili, English, French, and Gikuyu. Supports single-sentence and batch API input.

Current metrics (Apr 2026)

Language	F1	Precision	Recall	Samples
English	1.000	1.000	1.000	66
Swahili	0.851	0.822	0.881	67,290
French	0.970	1.000	0.941	165
Gikuyu	0.667	0.967	0.510	11,622

Live demo

https://huggingface.co/spaces/juakazike/gender-sensitization-engine

ML models

Model	Base	Val F1	Val Precision	Val Recall	Notes
sw-bias-classifier-v1	afro-xlmr-base	0.854	0.938	0.784	Full fine-tune, 51K rows
sw-bias-classifier-v2	afro-xlmr-base	0.953	0.940	0.960	Overfit on val — invalid
sw-bias-classifier-v3	afro-xlmr-base	0.871	0.810	0.942	Current deployed model

SW ML classifier is Stage 2 fallback only — runs when rules find nothing.

Architecture

• Detection: Deterministic lexicon rules (primary) + AfroXLM-R fine-tuned ML fallback (Swahili only)
• Correction: Word-level substitution with semantic preservation check (threshold 0.70)
• Languages: Separate lexicons per language — no cross-lingual transfer
• Context gating: 10 suppression conditions (biographical, quote, statistical, counter-stereotype, etc.)

API

POST /rewrite
{ "id": "1", "lang": "sw", "text": "Daktari wa kiume alifika" }

Returns: { original_text, rewrite, edits, confidence, source, reason }

Batch endpoint: POST /batch_rewrite (up to 50 sentences)

Dataset

• SW ground truth: 66,995 rows — Gold tier (sample count)
• KI ground truth: 11,622 rows — Bronze tier (sample count)
• All real text, no synthetic data. Sources: Helsinki Corpus, BBC Swahili, Wikipedia SW, AfriSenti, MasakhaNER
• Inter-annotator agreement (Cohen's κ): 0.8537 (Almost Perfect — AIBRIDGE Bronze threshold ≥ 0.61)

Run locally

pip install -r requirements.txt
uvicorn api.main:app --reload --port 8000   # API
python3 demo_live.py                         # CLI demo
python3 -m eval.evaluator                    # Run evaluation

AI BRIDGE submission

Team: JuaKazi | Updated: Apr 2026 | Schema: AIBRIDGE v1 (24-column CSVW)