A Walk Through the City of Edmonton
Bibliographic record
Abstract
As an industry placement through the WISEST Summer Research Program, an opportunity was provided to work with the City of Edmonton in an exploration of careers in engineering and architecture. The focus and scope of this placement was mainly centred around the Integrated Infrastructure and Engineering Services at the City. Through shadowing multidisciplinary engineers, technologists and architects, experience in both administrative and more hands-on work was gained. Some career pathways that were explored include materials engineering, geotechnical engineering, facilities (structural, mechanical and electrical) engineering, environmental engineering, geomatics engineering, and architecture. Throughout the duration of the program, information about the different roles and their collaboration with each other was gathered. Instead of performing research in labs, absorption of information was conducted mainly through means of observation. The City of Edmonton provided opportunities to attend various site visits, building and lab tours, and even to meetings in downtown. Tasks such as reviewing reports and drawings, attending meetings, and sitting in on business calls, all demonstrated the administrative nature of engineering and architecture. On the other hand, the more hands-on aspects of engineering were also emphasised through tasks such as assisting with field work, on-site testing, sample collecting, and data logging. With Integrated Infrastructure Services (IIS), the collaborative and interconnected nature of these careers were displayed, as each branch worked in conjunction with each other. The role of each different type of engineering and architecture is further defined in sequential order of the stages that leads to the life cycle of a construction project. This shows the direct results of each career field in contributing to the development, progression and completion of a project.
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 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".