Failing the duck test: Reply to Barbaro, Boutwell, Barnes, and Shackelford (2017).
Bibliographic record
Abstract
In this reply, we respond to the critique by Barbaro, Boutwell, Barnes, and Shackelford (2017) in regard to our recent meta-analysis of intergenerational transmission of attachment (Verhage et al., 2016). Barbaro et al. (2017) claim that the influence of shared environment on attachment decreases with age, whereas unique environmental and genetic influences increase, which they felt was disregarded in our meta-analysis. Their criticisms, we argue, are based on a misunderstanding of the core tenets of attachment theory. Barbaro et al. (2017) unify parent-offspring attachment, attachment representations, and romantic-pair attachment under the same conceptual and empirical umbrella, even though these constructs serve different behavioral systems. We show that excluding the incompatible twin data on pair bonding from their analysis undercuts their argument. Statements about the role of the shared environment in attachment beyond early childhood are highly uncertain at this point. Importantly, even if the role of the shared environment were to wane with age, its effects may still be causally important in later childhood or adult outcomes, as either an indirect factor or as a factor influencing earlier developmental outcomes. (PsycINFO Database Record
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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 | 0.019 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.055 | 0.074 |
| Insufficient payload (model declined to judge) | 0.009 | 0.010 |
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".