Replication studies of critical findings from the peer literature: An introduction.
Bibliographic record
Abstract
Despite its importance, replication has remained in the background of social development research. The aim of this special section was to elucidate and elevate the role of replication in peer relations research, examining its challenges and its utility for moving the field forward. To accomplish this aim, five sets of researchers undertook identifying an important finding from a widely cited article in the peer literature and tried to replicate its basic results using new data. As a group, the resulting five articles cover a broad range of topics, measures, and methods that are seen in peer research. Four of the five articles provide evidence of replication. This evidence was seen more for basic principles or processes observed in earlier studies than for exact or specific findings. In addition, the authors used varied approaches to replication, highlighting the need to embrace diverse methods when attempting to replicate complicated mechanisms of social development. It is argued that replication efforts should be aimed at identifying basic principles and processes of social development while clarifying the parameters that account for variability across studies in the specific findings. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.447 | 0.706 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.023 | 0.022 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.011 | 0.029 |
| Open science | 0.009 | 0.012 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".