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Record W2988792133 · doi:10.1130/ges02006.1

Making geoscience fieldwork inclusive and accessible for students with disabilities

2019· article· en· W2988792133 on OpenAlexaff
Alison Stokes, Anthony D Feig, Christopher L. Atchison, Brett Gilley

Bibliographic record

VenueGeosphere · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFlexibility (engineering)PaceFocus groupInclusion (mineral)PerceptionEarth sciencePsychologyPedagogyMedical educationSociologyGeologyMedicineManagement

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0050.003
Open science0.0010.012
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.042
GPT teacher head0.431
Teacher spread0.389 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations114
Published2019
Admission routes1
Has abstractyes

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