Some thoughts on essence placeholders, interactionism, and heritability: Reply to Haslam (2011) and Turkheimer (2011).
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the target article (Dar-Nimrod & Heine, 2011), we provided a social-cognitive framework which identified genetic essentialist biases and their implications. In their commentaries, Haslam (2011) and Turkheimer (2011) indicated their general agreement with this framework but highlighted some important points for consideration. Haslam suggested that neuroessentialism is a comparable kind of essentialist bias and identified similarities with the genetic essentialism framework. In response, we acknowledge similarities but also identify qualitative and quantitative differences between genetic essentialism and other kinds of essentialist biases. Turkheimer challenged us to extend our discussion to address the question of how should people respond to genetic etiological information, critiqued the use of heritability coefficients, and identified a new construct (1 - rMZ), which may be termed a free-will coefficient. In response, we emphasize the need to transform interactionist explanations from being empty platitudes to becoming the default conceptual framework; we wholeheartedly accept his critical view of heritability coefficient estimates (but acknowledge a more limited utility for them); and we are intrigued by his conceptual interest in identifying free-will coefficients yet warn against falling into pitfalls similar to those that were stumbled into in the past.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.006 |
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 it