Discussion and Implications for Practice: Women Student Veterans and their Sense of Identity, Belonging, and Voice in Writing Courses and through Writing Assignments
Bibliographic record
Abstract
Given the lack of published research on women student veterans as a group separate from men student veterans and the unique needs of women student veterans, individual attention needs to be paid to women student veterans. This qualitative study used feminist critical theory to examine the experiences of women student veterans during their transition process from the military to higher education regarding identity, belonging, and voice in connection with writing courses and writing assignments. Real-time in-depth narrative interviews were conducted with seven current or former women student veterans located across the United States. Analysis of the interviews revealed superordinate themes. These three superordinate themes were 1) military influence: lifestyle transition, identity, and writing; 2) peer connections in writing courses; and 3) writing instructor influence. The findings informed by the superordinate themes included women student veterans sometimes have difficulty transitioning from military writing to academic writing, women student veterans need peer connections in the writing classroom, and writing instructors hold much influence over belonging and voice for women student veterans. These findings led to three recommendations for future practice. The first recommendation was that writing workshops focusing on the differences between military writing and academic writing should be held for women student veterans by individual colleges and universities. The second recommendation was colleges and universities can establish and maintain writing groups for women student veterans in which they write and share narratives and poetry reflective of their military and other life experiences. The third recommendation was writing instructors should be trained on providing women student veterans with individualized attention and supportive feedback. Keywords: women student veterans, writing courses, identity, belonging, voice
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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 | 0.065 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.025 | 0.019 |
| Scholarly communication | 0.018 | 0.032 |
| Open science | 0.008 | 0.016 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".