Bibliographic record
Abstract
Abstract The Canadian Astronomical Society/Societe Canadienne d’Astronomie (CASCA) is the organization of professional astronomy in Canada. In 2015, CASCA created an Equity and Inclusivity Committee, with a mandate to collect data, track progress, propose initiatives and promote equity, diversity and inclusion (EDI). The committee has now been active for several years and has recently completed the first climate survey of its members. The climate survey in particular highlighted the difference experiences of those identifying as women and men within the astronomical community. Attempts to revive demographics studies of the society have been met with several challenges, recognizing today the need for individuals to self-identify. We describe as well the planned emphasis on EDI within Canadian astronomy’s next decadal style survey. Finally, we note initiatives of Canada’s funding agency for astronomy, NSERC, and individual initiatives that have been undertaken. EDI is a priority for CASCA, and there is a lot of motivation and lots of ideas for improvement. Solutions will take time, cooperation and money to implement.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.025 | 0.011 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".