A review of the non-equivalent control group post-test-only design
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
BACKGROUND: Quantitative research designs are broadly classified as either experimental or quasi-experimental. The main distinguishing feature of the quasi-experiment is the manipulation of the independent variable without randomisation. When randomisation or use of a control group is unfeasible, a researcher can choose from a range of quasi-experimental designs. AIM: To present the features of the quasi-experimental 'non-equivalent control group post-test-only' design, which aims to demonstrate causality between an intervention and an outcome. DISCUSSION: This paper provides an overview of the non-equivalent control group post-test-only design in terms of its design features, applications and statistical analysis, as well as its advantages and disadvantages. CONCLUSION: The non-equivalent control group post-test-only design can be used in natural settings, where randomisation cannot be conducted for ethical or practical reasons. Although the design is less complex than some other designs, with low error propagation, it is vulnerable to threats to internal validity.
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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 | 0.028 | 0.463 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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