Making geoscience fieldwork inclusive and accessible for students with disabilities
Bibliographic record
Abstract
Abstract Fieldwork is a fundamental characteristic of geoscience. However, the requirement to participate in fieldwork can present significant barriers to students with disabilities engaging with geoscience as an academic discipline and subsequently progressing on to a career as a geoscience professional. A qualitative investigation into the lived experiences of 15 students with disabilities participating in a one-day field workshop during the 2014 Geological Society of America Annual Meeting provides critical insights into the aspects of fieldwork design and delivery that contribute to an accessible and inclusive field experience. Qualitative analysis of pre- and post-fieldwork focus groups and direct observations of participants reveal that multisensory engagement, consideration for pace and timing, flexibility of access and delivery, and a focus on shared tasks are essential to effective pedagogic design. Further, fieldwork can support the social processes necessary for students with disabilities to become fully integrated into learning communities, while also promoting self-advocacy by providing an opportunity to develop and practice self-advocacy skills. Our findings show that students with sensory, cognitive, and physical disabilities can achieve full participation in field activities but also highlight the need for a change in perceptions among geoscience faculty and professionals, if students with disabilities are to be motivated to progress through the geoscience academic pipeline and achieve professional employment.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".