The current state of gender-based diversity within the field of Canadian professional structural timber engineering
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
There is currently minimal data that may be used for retention and recruitment strategies for timber professional engineering in Canada. A comprehensive survey performed in 2022 to address this lack of data are discussed. The survey was generated and analyzed by York University (Canada) and distributed through the Canadian Wood Council’s membership directory. This survey explored participants’ motivations for working on timber-based structural projects and the existing state of EDI training within the workspace. Findings from the context of analysis illustrated that retention in the work force appears not to be affected by gender, with participants overwhelmingly indicating their plan is to continue to work in the timber structural engineering sector. Gender specific findings suggest that most men who practice timber structural design have had more recorded work experience, whereas women were more likely to obtain a PhD when pursuing graduate school.
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.
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 | 0.001 | 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) | 0.000 | 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