Perception doesn't match reality: Unraveling gender disparities in Earth scientists' productivity during work-from-home initiatives
Bibliographic record
Abstract
Abstract Work-from-home initiatives have led to a disproportionate impact among different genders. An individual's perception of their own productivity is significant in understanding how equity-deserving groups are affected by disruptions to normal routines. The term “equity-deserving groups” is common in Canadian academia and is used at Queen's University to convey that seeking equity should not be placed on the group, but rather on systemic, cultural, and societal change. Despite many faults, peer-reviewed publications are a key metric of academic productivity, as they are a vital component of career advancement. Using methods based on sex (female versus male) and gender (women versus men), this study investigates how both the perceived and measured productivity of Earth scientists was impacted by global COVID-19 work-from-home initiatives. Bibliometric and survey-based data are used to evaluate and compare the productivity of Earth scientists. Although there are inherent flaws in directly comparing sex and gender, the results of this study contribute to the understanding of how sex- and gender-minorities have been impacted by work-from-home initiatives. Our research shows that in a normal year, females publish proportionally to males, and that the proportion of female first authors increased between the 2019–2020 (“pre-pandemic”) and 2020–2021, 2021–2022, and 2022–2023 (“during pandemic”) years. This finding is contrary to the perceived productivity between women and men and indicates that our perceptions may not always match reality. Although women and men are publishing at nearly identical rates based on their proportions within our field, women perceive themselves as less productive, which creates a disconnect between perception and the data. We posit that the more negative perception of self-productivity among women and early-career researchers can lead to mental health issues and a lack of confidence. Support structures should therefore be focused on these groups to ensure more equitable outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".