Bibliographic record
Abstract
Programming languages are being taught and studied for more than 30 years in the graduate seminar on Programming Language Design. Students have studied the structure and design of programming languages from a human and linguistic perspective. Beginning at the University of Toronto in the mid-70's, this course has continued to interest generations of graduate students in computing at Queen's University since 1986. Every year, students study Wegner's Milestones in the History of Programming Languages to set the tone and foundation of the course, and propose their own more recent milestones to follow on Wegner's list. This document contains the “Milestones and comparisons” of more recent languages chosen by the class of 2008. This book is authored and edited by members of the class of fall semester 2008 at Queen's University, under wise guidance and teaching of Prof. Dr. Jim Cordy. It reviews a number of modern programming languages using the same timeless criteria outlined by Weinberg in 1971, based on human psychology and the linguistics of natural languages.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.016 |
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".