Methods before metrics

How WaitGraph measures a wait

A useful waiting-time answer starts with an exact process, keeps different evidence classes separate, and remains honest about cases that have not finished.

01 · Define the interval

Every process needs a start and an end

WaitGraph measures elapsed time between a named start event and a named first outcome. Similar labels are not automatically comparable: account setup, identity checks, appeals, site review, and time until earnings can be separate processes.

StartSubmitted and acknowledged
EndFirst defined verdict or outcome

02 · Label the source

Four evidence classes, never blended

An answer belongs to exactly one class. Text labels remain visible beside every result.

ClassMeaningExample label
Official estimateGuidance published by the organization or another authoritative source.Google’s published timeframe
AI-sourced general answerA current answer synthesized from cited public sources; not WaitGraph data.Published guidance — no WaitGraph estimate yet
Documented patternReal observations exist, but volume or contributor diversity is insufficient for a population estimate.Repeated observed cycles from one contributor
WaitGraph estimateEnough recent, comparable tracked cases exist for a defensible statistical estimate.Based on recent cases from distinct contributors

03 · Keep unfinished waits

Still waiting is data, not a missing row

An active wait is right-censored: it has lasted at least this long, but its final duration is unknown. Calculating only from people who already finished would bias the answer downward.

WaitGraph preserves prospective, late-active, and retrospective registration modes. As queues mature, time-to-event analysis uses active cases, day-level precision where needed, contributor clustering, cohort boundaries, recency windows, and process-version breaks.

04 · Earn publication

Queue gates

Counts are minimum gates, not automatic publication rules. Every state change requires an auditable reason and editorial review.

StateDefault gatePublic behavior
RequestedUnsupported demand onlyNo indexable page by default
Forming3 legitimate active trackers, or 10 distinct demand events from 5 likely-distinct sessions in 30 daysGuidance and collection status; no estimate
Documented patternRepeated useful evidence but insufficient contributor diversityExact observation with a prominent limitation
EarlyAt least 5 accepted completions from at least 3 contributors, including prospective or system-tracked casesCounts and distribution cautiously; no live claim
PreliminaryAt least 10 comparable completions from at least 5 contributorsCautious range after manual review
LiveAt least 30 recent comparable completions from at least 10 contributors; at least half prospective or evidence-backedCurrent estimate with uncertainty after editorial review
High confidenceAt least 100 recent completions from at least 40 contributors plus effective-sample, evidence, and freshness gatesStronger confidence label
StaleFreshness or process-version gate failsKeep history; withdraw the current estimate
ArchivedThe process ended or materially changedPreserve history and link to a replacement

05 · Show the denominator

Statistics and uncertainty

Eligible live queues can report median time, interquartile range, milestone waiting shares, active censored count, raw cases, distinct contributors, evidence composition, analysis cutoff, and freshness. Percentiles appear only when the data can estimate them responsibly.

Evidence tiers may support sensitivity checks, but weighting cannot repair contributor concentration. Credible long waits are not deleted merely for looking unusual. A case is excluded only for a documented reason such as duplication, wrong process, invalid endpoints, or manipulation.

Corrections are part of the method

Sources and process boundaries change.

WaitGraph records source-check dates, evidence reviews, methodology versions, and correction events. A correction should leave an audit trail instead of silently rewriting history.

Review correction policy