Bibliographic record
Abstract
Historically speaking, men dominated the university sphere and women were not typically present in academic positions (Ward & Wolf-Wendel, 2012). The dominance of male academics lead to gendered norms and expectations that influence academic life presently (Jakubiec, 2015). Today, more women are entering into higher education as students and as professors; however, sexism and gendered notions about women have not been eradicated (Rhoads & Rhoads, 2012). Further, it is especially difficult for women who are mothers to succeed, get promoted, and achieve tenure. For example, women (more so than men) have reported that parenthood and childbearing are main barriers in their attainment of full professorship (Sanders, Willemson, & Millar, 2009). In fact, Dryfhout and Estes (2010) found that professors who were women were 30% less likely to have attained tenured faculty positions, and were also more likely to have intentions to leave the academic profession. Thus, the impacts of having children on an academic career may be greater for women then it is for men. Thus, what can be said for the state of academic motherhood in Atlantic Canadian universities?
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.028 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".