VIRTUAL LYLE: ARCHITECTURE TRANSFORMED AN ONLINE EXHIBITION INFORMED BY A THREE-STAGE USER STUDY
Bibliographic record
Abstract
to lend or sell copies of this dissertation in paper, microform or electronic formats, and b) LIBRARYAND ARCHIVES CANADA to reproduce, lend, distribute, or sell copies of this dissertation anywhere in the world in microform, paper or electronic formats and to authorize or procure the reproduction, loan, distribution or sale of copies of this dissertation anywhere in the world in microform, paper or electronic formats. The author reserves other publication rights, and neither the dissertation nor extensive extracts from it may be printed or otherwise reproduced without the author’s written permission. Certificate Page This thesis proposes to design an online exhibition by developing a protocol for a front end user study that engages a group of computer and design-literate end users. The creation of online exhibits is usually the task of generalist multimedia designers working with specialist curators. Once online, the success of these sites has been tested through post-mortem evaluations that contribute to future efforts but have little effect on the original site. While the use of front-end focus groups is increasing, these are limited in value because of the difficulty target audiences have in visualizing the possibilities that the technology offers. This thesis utilizes the opportunity to develop an online exhibit in collaboration with its potential end-users. The resulting website is reflective of the latest theoretical and technological advances, while the three-stage user study developed here can serve as a model for future such endeavours. iv
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 | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".