Research
Patterns are counts, not conclusions.
A future research layer would summarize anonymized structure across many discovery files: which issue categories recur, in which states, in which years, and where contract language is materially similar. It would never expose a narrative, a document or an identity.
Every figure on this screen is fabricated for demonstration. No real carrier, agency, or platform statistics are represented.
Issue categories
Files by year of events
Geography
- Texas22 files
- Florida18 files
- Ohio13 files
- Arizona11 files
- Georgia9 files
Anonymized cohorts
Retroactive compensation adjustment · 2023–2025
cohort size 34
High contract-language similarity across 21 of 34 files
17 resolved internally · 9 in counsel review · 8 no reported outcome
Termination notice shorter than agreement interval
cohort size 19
Shared clause phrasing detected in 12 agreements
8 resolved internally · 6 in counsel review · 5 no reported outcome
Deferred compensation forfeiture at exit
cohort size 26
Comparable forfeiture language in 15 agreements
11 resolved internally · 10 in counsel review · 5 no reported outcome
What these panels cannot tell you
- Whether any organization acted improperly
- How common an experience is across the real industry
- The outcome of any individual matter
- Anything about a contributor's identity or narrative
Method
What would make a pattern publishable.
Minimum cohort size
No pattern is shown below a threshold that could re-identify a contributor.
Consent-scoped inclusion
Only files explicitly marked aggregate-eligible are counted, and removal is retroactive.
Stated limitations
Every figure would carry its denominator, its date range, and what it cannot support.