layoff-watch

Methodology

layoff-watch produces three scores per company — 6-month, 12-month, 24-month — based on a deterministic rules engine over publicly observable signals. There is no LLM in the scoring pipeline. Every score is reproducible byte-for-byte from its signal run.

Sources

Scoring

Each company starts at a baseline of 50. Each rule that fires adds (or subtracts) a contribution per horizon. The final score is clamped to 0–100.

Rule weights

Rule6m12m24m
news_layoff_recency
news_layoff_history
news_closure_recency
news_growth_counter
jobs_30d_decline_sharp
jobs_90d_decline_sustained
jobs_growth_counter
anaf_headcount_drop
anaf_revenue_drop
anaf_loss_streak
reddit_layoff_mention_fresh
reddit_departure_cluster
reddit_rto_mention
glassdoor_keyword_layoff
glassdoor_rating_drop_significant
glassdoor_review_volume_spike
undelucram_keyword_layoff
undelucram_rating_drop_significant
undelucram_review_volume_spike

Weights shown above reflect what a rule will add when it fires. Rules that emit no contributions on empty input show "—".

Confidence

Each horizon has its own confidence (low/medium/high) derived from signal coverage. Companies with insufficient signals do not show a numeric score — the UI displays "Not enough signals to score" instead.

Disclaimer

layoff-watch publishes signals, not predictions. Scores describe observable public information and do not predict the future. If you believe a signal is wrong, use the "Request correction" form on the company page.