Mechanical TA 2: Peer Grading with TA and Algorithmic Support
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
Mechanical TA 2 (MTA2) is an open-source, distributed peer grading system that boosts performance by leveraging both trusted TAs and computationally intensive algorithms. The system provides a unified platform for submission of assignments, grading by both peers and TAs, and reporting of feedback. It also supports dividing students into different pools based on their peer-grading prowess; mechanisms for automated calibration and spot checking; and the ability for students to appeal grades and to give feedback about individual reviews. Bayesian inference and mixed-integer programming algorithms perform interpretable aggregation of peer grades and estimate students' grading performance, providing feedback, incentivizing high-quality grading, and directing TA spot checks appropriately. Analysis of data from four offerings of a large undergraduate class provides empirical evidence of MTA2's effectiveness.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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