Bibliographic record
Abstract
A principal objective for Merrill-Palmer Quarterly during this editorial term is to maintain the standards of excellence established by the past Editor, Dr. Carolyn U. Shantz, and continue to advance the scope and quality of scholarship that appears in the journal. This aim has been at the forefront of Merrill-Palmer Quarterly's nearly 50 years of existence, and as a result, the journal's readership, submission rates, and scholarly reputation have grown substantially. MPQ is now ranked among the most respected journals in the human developmental sciences (see Rushton & Roediger, 1978; Feingold, 1989; and Howard & Day, 1995, see p. 141). Another objective is to expand the scope of the journal's content so as to embrace diverse academic disciplines, research contexts and paradigms, and geo-political perspectives, while also refining its mission by featuring articles in which authors initiate important new areas of inquiry, transcend traditional disciplinary boundaries, and introduce conceptual, methodological, and analytic innovations. Toward this end, the Editors seek to establish a format for the journal that is diverse with respect to contributors' and readers' scientific disciplines, professional status (junior versus senior investigators), ethnicity and cultural backgrounds, and geo-political contexts or locations. Included in this aim is the goal of publishing contributions from a global community of scholars; the Editors encourage submissions from investigators who reside or work in countries other than the USA and Canada.
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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 | 0.006 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.117 | 0.072 |
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".