Persimmon: Nested Family Polymorphism with Extensible Variant Types
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
Many obstacles stand in the way of modular, extensible code. Some language constructs, such as pattern matching, are not easily extensible. Inherited code may not be type safe in the presence of extended types. The burden of setting up design patterns can discourage users, and parameter clutter can make the code less readable. Given these challenges, it is no wonder that extensibility often gives way to code duplication. We present our solution: Persimmon, a functional system with nested family polymorphism, extensible variant types, and extensible pattern matching. Most constructs in our language are built-in "extensibility hooks," cutting down on the parameter clutter and user burden associated with extensible code. Persimmon preserves the relationships between nested families upon inheritance, enabling extensibility at a large scale. Since nested family polymorphism can express composable extensions, Persimmon supports mixins via an encoding. We show how Persimmon can be compiled into a functional language without extensible variants with our translation to Scala. Finally, we show that our system is sound by proving the properties of progress and preservation.
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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 | 0.001 | 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