Merging Territories, Part III: Reaching Maturity and Responding to Change
Bibliographic record
Abstract
This article reflects upon the ongoing development of the Information Design (ID) program at Mount Royal University. The development of the ID program is discussed in two previous IPCC publications in 2008 and IPCC 2012. The program is the result of over a decade of development and refinement. Technical writing, technical communication, electronic publishing and design expertise, all contributed to the creation of the new degree. This degree has faced academic scrutiny in program reviews. A mandated program review is described and the resulting recommendations highlighted. Student NSSE data for 2017 and 2018 is presented for comparison with the university population. A new Information Design minor launches fall 2020 to meet requests from other programs. Changing economic conditions in new workplace expectations drive possibilities for future collaboration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.051 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.023 | 0.030 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".