Ongoing story · 10 developments
Cases
Tracked since . Each development below is a separately scored story with its own sources — this page only groups them so the running story doesn’t crowd the main feed.
Latest development
· Free Press Journal
Timeline
- Mumbai Sees Drop In Crimes Against Women, But False Promise Of Marriage Cases Rise Sharply: Police Data
Limited reporting491 outlets
- Technical Lapses Trigger Acquittals In 10 Of 14 Mumbai Narcotics Cases This Year
Limited reporting491 outlets
- Mumbai Police Registers Over 3,400 Drug Consumption Cases In Six Months, Outnumbering Possession Offences
Limited reporting491 outlets
- World Head And Neck Cancer Day 2026: Experts Urge Early Detection As India Records 77,000 Oral Cancer Cases Annually, 15 Per Cent Recurrence
Limited reporting431 outlets
- Fast-Track Courts, Slow Justice: Mumbai’s Biggest Financial Fraud Cases Still Await Trials
Limited reporting491 outlets
- England's World Cup Defeats Trigger Record Spike In UK Domestic Abuse As Police Record 384 Cases
Limited reporting491 outlets
- 'Over 96,000 Cases Pending In Supreme Court, 26 Await Disposal For More Than 30 Years': Law Minister Arjun Meghwal
Limited reporting491 outlets
- India's Exam Fraud Bubble: 148 Cases, One Conviction in 11 Years
Uncorroborated0 outlets
- Pune: Dengue Cases Surge In July As Intermittent Rains Boost Mosquito Breeding
Limited reporting491 outlets
- 550 Dengue Cases In State; AI, Drone Mapping To Aid Prevention
Limited reporting491 outlets
Reporting confidence
49/100- Corroboration
- 15/40
- Source reliability
- 19/30
- Primary source
- 0/15
- Headline check
- 15/15
1 independent reporting origin across 1 outlet — shared ownership, reprinted wire copy, and articles citing another outlet’s reporting count once.
Headline check performed by keyword heuristics. How scoring works →
Score shown is for the latest development only — each entry in the timeline has its own independent score. Grouping into this hub does not affect any individual story’s score. How hubs work →
KhabarCheck groups developments automatically by shared, specific detail — not just a shared topic — so unrelated stories that happen to mention the same name or institution don’t get lumped together. This grouping can occasionally miss a development or split one by mistake; read the method.