The automated checks.

Twenty-one automated checks run on every response. All of them, with their weights, are open for inspection under Signal weights on the Respondent Risk tab; the groups below mirror that panel exactly. Each weight is the check's ceiling: graded checks award a share of the weight by severity, so a mild speeder scores far less than an extreme one.

Check Weight What it catches
Traps & rules
Failed a trap 90 Claimed a decoy brand, failed an attention check, or tripped a logic rule set on the Traps tab. Effectively conclusive.
Quality-fail tag 90 A hand-applied quality tag from the survey team. A human verdict, so effectively conclusive.
Logical impossibility 45 Age contradicts birth year, an allocation grid that does not sum to 100, a number outside anything else in the sample.
Speeders
Speeder 70 Finished far under the median duration. Graded: the further below the threshold, the more of the weight they score.
Skimmer 70 Too little time per question actually answered. Catches racers on long paths whose total time looks normal.
OE checks
Bad open-ends 70 Scored on the share of a respondent's text answers carrying red flags, verified on the OE Checks tab.
OE duplicate (corroborated) 60 Shares a written answer with someone AND agrees with them beyond chance elsewhere. A lone shared answer is only an amber OE flag.
Straightlining
Straightlining 40 Flat, patterned or diagonal answering on grids. Low-differentiation grids are soft yellows, since using two scale points is often honest.
Duplicates
Device duplicate 70 Same device fingerprint twice in one wave. The first entry keeps a soft 10 as the original; later entries take the full weight.
Panel-id duplicate 70 Same panel id on a different device: the panelist coming back a second time where the fingerprint cannot see it.
Patterns
Near-identical answer profile 70 A respondent's whole closed profile matches another respondent far beyond chance. Scored higher when the two also arrived within minutes of each other.
Careless responding 45 Psychometric evidence of not reading: uncorrelated related items, inconsistent halves, outlier answer profiles.
Erratic answering 35 Within-person variability far above the sample: random clicking, which never straightlines and never speeds.
Response style 15 Extreme, midpoint or acquiescent responding well beyond the sample. A style, not necessarily fraud, so kept low.
Improbable profile 35 Low-probability options chosen right through the survey, standardised per question.
Over-claiming 35 Ticks far more multi-select options than peers. Fifteen of seventeen brands when the average is three or four.
Timing
Duration cluster 30 Total duration near-identical to an unusual number of other respondents: a script signature.
Entry burst 25 Started within two minutes of many others on one channel. Weak on purpose: panels legitimately launch in bursts.
Impossible duration 55 Reported duration longer than the wall-clock time between start and finish. Reads 0 on Glow-collected data by construction; it exists to catch imported files with forged durations.
History & returning panelists
On the blocklist 75 Device was removed from an earlier study and banked on the cross-project blocklist.
Attribute drift 25 A returning panelist who changed an answer returners almost never change (birth year, postcode). Deliberately low: a lead to check, not a verdict.

Tuning weights and thresholds

Every weight and threshold is editable, per survey. Two common adjustments:

  • Speeders and skimmers default to flagging anyone who finished under 40% of the median duration. On a long or repetitive survey honest respondents can legitimately race, so dropping the line to 33% narrows the net to the extreme cases; on a short, rich survey the default is usually right.
  • Straightliners require a minimum of 8 statements per grid by default, which suits same-valence batteries (all positively worded). For mixed-valence grids (positive and negative statements mixed) a flat line is much stronger evidence, so dropping the minimum to 5 is reasonable.

Rule of thumb: tune thresholds before you start deleting, not after. Changing a threshold rescores the sample, and you want your verdicts recorded against the scoring you actually used.

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