Becoming Through Story: The Relational Processes of Writing and Creating the StOries Project
Bibliographic record
Abstract
Abstract This final chapter is not a typical recapitulation of the stories and ideas presented in this anthology. Rather it is a storied approach to reflecting on the relational processes of the StOries project, in order to contemplate what we have learned and to propose where we might go from here. I interweave my own reflections (and diffractions) of the challenges faced in writing this discussion of ‘fieldnotes’ that a number of authors submitted to describe their own writing processes. I also showcase examples of methods used in the project to illustrate how we generated meaningful introductions and discussions about identity, intersectionality, home, and belonging (among other things). Ideally the chapter will be read not as a conclusion, but as an opening to new ways of viewing ourselves and each other in the context of migration research. It also aims to promote the Indigenization of migration scholarship and the institutions that teach and create this scholarship, and to encourage discussions and changes in how we view people who migrate.
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 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".