A collaborative autoethnographic journey of collective storying: Transitioning between the ‘I’, the ‘We’ and the ‘They’
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The story we share here is about lessons learned during a three-year, collaborative autoethnographic journey beginning in January 2020. Our story is one of conducting a meaningful inquiry into our shared lived experience amid the changes brought about by COVID-19 lockdowns. Our insights speak to how we collaboratively reflected and researched across institutions, countries, disciplines, and career stages. More importantly, in making our process explicit, we highlight the way storying was experienced within our collective space. In doing so, we explore insights about how stories are adapted and transformed through a process of navigating the development of, and transitions between, pre-public and public spaces. Using an Arendtian lens, we explore the question, How are autoethnographic collaborative stories crafted for research in an academic context? Our insights present a cyclical and developmental frame within which to process collaborative storying and indeed collaborative academic work.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it