Chasing the Anchor: A Systematic Review and Meta-analysis of Perceptual Anchoring Deficits in Developmental Dyslexia
Bibliographic record
Abstract
We report the results of a systematic review and meta-analysis investigating the relationship between perceptual anchoring and dyslexia. Our goal was to assess the direction and degree of effect between perceptual anchoring and reading ability in typical and atypical (dyslexic) readers. We performed a literature search of experiments explicitly assessing perceptual anchoring and reading ability using PsycInfo (Ovid, 1860 to 2020), MEDLINE (Ovid, 1860 to 2019), EMBASE (Ovid, 1883 to 2019), and PubMed for all available years up to June (2020). Our eligibility criteria consisted of English-language articles and, at minimum, one experimental group identified as dyslexic - either by reading assessment at the time, or by previous diagnosis. We assessed for risk of bias using an adapted version of the Newcastle-Ottawa scale. Six studies were included in this review, but only five (n = 280 participants) were included in the meta-analysis (we were unable to access the necessary data for one study).The overall effect was negative, large and statistically significant; g = -0.87, 95% CI [-1.47, 0.27]: a negative effect size indicating less perceptual anchoring in dyslexic versus non-dyslexic groups. Visual assessment of funnel plot and Egger’s test suggest minimal bias but with significant heterogeneity; Q (4) = 9.70, PI (prediction interval) [-2.32, -0.58]. The primary limitation of the current review is the small number of included studies. We discuss methodological limitations, such as limited power, and how future research may redress these concerns. The variability of effect sizes appears consistent with the inherent variability within subtypes of dyslexia. This level of dispersion seems indicative of the how we define cut-off thresholds between typical reading and dyslexia populations, but also the methodological tools we use to investigate individual performance.
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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 | 0.028 | 0.072 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".