Coming in from the cold: Addressing the challenges experienced by women conducting remote polar fieldwork
Bibliographic record
Abstract
Remote fieldwork is an important component of polar research across both physical and social sciences. There is increasing recognition that the inherent logistical, physical, psychological, and interpersonal challenges of remote polar fieldwork are not felt equally across the polar research community, with minority groups often disproportionately affected. Although historically lacking diversity, the demographics of polar researchers have shifted, and the way polar research is conducted has been changing in response. However, there are still barriers to equal participation. Removing these barriers would attract scientists from more diverse backgrounds and improve scientific outcomes. We explored the lived experiences of those who identify as women in polar fieldwork through a review of current literature and an anonymous survey, using existing networks to connect with women working in polar research. We synthesised survey responses with regards to topics such as harassment, hygiene, inefficient communication, gendered work expectations and responsibilities to form a holistic understanding of the key fieldwork challenges faced by women. The majority of survey respondents (79%, n = 320) had encountered negative experiences during fieldwork, with the most common and impactful issues relating to field team dynamics and communication, sexism, rest, and weather. Many other issues including fieldwork preparation, work expectations, harassment, and personal space and privacy were also raised by respondents. We identify critical points of action from the survey results and in literature and propose strategies to remove barriers to participation and improve the experiences of women in polar fieldwork. These include individual- and organisational-level strategies for pre, during, and post fieldwork. A diverse polar research community is imperative in order to address the challenges presented by current unprecedented climate change. Though this study focussed on women’s experiences, we seek to advance the discourse on challenges faced by all minorities in polar research.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".