A Shared Cabin in the Woods
Bibliographic record
Abstract
In this paper, we investigated a model of academic development based upon a recurring residential academic writing retreat combining individual writing times, workshops, work-in-progress groups and one-on-one consultations with shared meals and informal gatherings in a natural environment. Using a case study research approach, we analysed data accumulated from seven annual residential writing retreats for education scholars. Participants included 39 academics, administrative staff, senior doctoral students and community partners from multiple institutions. We found evidence that the retreats enhanced participants’ knowledge of writing and publishing processes, advanced their academic careers, built scholarly capacity at their institutions and strengthened writing pedagogy. The data indicated that the presence of writing and writers at the residential academic writing retreats generated presents (i.e., gifts) for the participants. The presence of writing time, writing goals and writing activities in the company of other writers were key to the retreat pedagogy. Participants appreciated gifts of time and physical space and described giving and receiving peer feedback and emotional support as forms of gift exchange within the community. The resulting writing strategies, competencies and identities provided the gift of sustainability. The analysis confirmed that this ongoing, immersive, cross-institutional, cross-rank, institutionally funded model of academic development was effective and responsive to the needs of individual scholars.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".