Individual differences in face processing ability and consistency in visual strategies
Bibliographic record
Abstract
Individual differences in face processing ability are a useful tool to better understand the cognitive and perceptual mechanisms involved in optimal face processing (e.g. see Yovel et al., 2014). We recently showed using the Bubbles technique (Gosselin & Schyns, 2001) that these individual differences are linked to a quantitative increase in the use of the eye area of faces, a feature known to be highly diagnostic for accurate face recognition (Royer et al., VSS 2016 meeting). However, no specific visual strategy was found in the lower recognition ability observers, possibly due to the use of inconsistent visual strategies in these individuals. This inconsistency could manifest at different levels, namely (1) between subjects, i.e. lower ability individuals rely on idiosyncratic recognition strategies, or (2) within subjects, i.e. lower ability individuals show an unstable pattern of diagnostic information throughout the bubbles task. The present experiment directly investigates these propositions. Fifty participants (28 women) were first asked to complete 2000 trials of a 10-alternative forced choice face recognition task in which the stimuli were randomly sampled using Bubbles. All participants also completed three common face matching and recognition tests to quantify their face processing ability. First, between-subject consistency in visual strategies in observers with similar levels of identification performance was strongly correlated with general face processing ability (r = .69; p < .001). Moreover, this inconsistency in visual strategies was also present at the within-subject level. Indeed, face processing ability was also significantly correlated with each observer's level of consistency in their own visual strategies throughout the bubbles task (r = .42; p = .002). These results demonstrate that while higher ability face recognizers consistently use a similar and stable strategy to recognize faces, lower ability individuals instead rely on idiosyncratic and varying strategies, possibly reflecting the imprecision of their facial representations. Meeting abstract presented at VSS 2017
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".