PhD students in CSD (Covington & Jordan, 2022)
Bibliographic record
Abstract
Purpose: The COVID-19 pandemic upended the status quo in higher education, causing rapid and unprecedented instructional, social, and financial changes. The aim of this exploratory study was to characterize doctoral students’ experiences during the pandemic and draw insights that may impact the long-term health of the field of communication sciences and disorders (CSD).Method: One hundred sixty current PhD students in CSD completed an online survey. Student perceptions of the pandemic’s impacts on their academic progress, future academic careers, and support from their academic programs were analyzed both quantitatively and qualitatively.Results: A majority of students indicated that the pandemic had negatively impacted progress through their PhD program. A quarter of respondents reported that their caregiving responsibilities had increased. Of these, the majority said that this increase in caregiving would delay their academic progress. A majority of students had concerns about farther-reaching negative impacts on their academic careers. Students’ perceived support from their programs during the pandemic was significantly lower compared to perceived support prior to the pandemic. When asked directly what decision-making stakeholders should know, respondents reported increases in stress and anxiety, a desire that stakeholders would recognize the effect of less-rich academic environments on student training, and the potential that students would leave the academic “pipeline” as a result of pandemic-related delays and stressors. Across multiple open-response questions, students expressed concerns that the negative impacts of the pandemic would be unequally distributed across groups, such that existing inequalities in academia would be further exacerbated by the pandemic.Conclusion: This study characterizes the lived experiences of PhD students in CSD during the COVID-19 pandemic and provides information that may inform key decision-making stakeholders (advisors, departments, and the American Speech-Language-Hearing Association) as they continue to make changes and accommodations in response to the pandemic. Supplemental Material S1. Survey instrument. Supplemental Material S2. Qualitative methods and limitations. Supplemental Material S3. By-question thematic analyses. Covington, N. V., & Jordan, L. M. (2022). Impact of the COVID-19 pandemic on PhD students in communication sciences and disorders. Perspectives of the ASHA Special Interest Groups. Advance online publication. https://doi.org/10.1044/2021_PERSP-21-00137
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.343 | 0.090 |
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".