Bibliographic record
Abstract
Abstract We present new opportunities for psycholinguistic research that are made available by presenting experiments online over the web. We focus on PsychoPy3, which is a new version of a system for the development and delivery of behavioural experiments. Crucially, it allows for both these functions to be performed online. We note that experiments delivered over the web have significant efficiency advantages. They also open up new opportunities to increase the ecological validity of experiments and to facilitate the participation of members of populations that have thus far been less studied in the psycholinguistic literature. We discuss the crucial matter of millisecond timing in online experiments. The technical details of implementation of a behavioural psycholinguistic experiment are presented, along with listings of additional technical resources and support. Our overall evaluation is that although online experimentation still has technical challenges and improvements are ongoing, it may well represent the future of behavioural psycholinguistic research.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.361 | 0.196 |
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".