Bibliographic record
Abstract
The concept of story draws attention to the relationship between personal experience and expression, and the broader contexts within which such experiences are ordered, performed, interpreted, and disciplined. In the past, particularly through the ‘cultural turn’, geographers were predominantly concerned with the ways in which story and storytelling were implicated in the production of cultural, economic, political, and social power. Today, this approach to story is being re-examined and new approaches to story are being explored. Geographers have been re-imagining the concept of story as part of a relational and material turn within the discipline, as part of a renewed focus on the political possibilities afforded by storytelling, and as a mode of expressing non-representational, (post)phenomenological geographies. This paper contextualizes recent work within broader disciplinary trends and critically evaluates the intellectual and political stakes of these new geographies of story and storytelling. It questions whether a shift away from understanding stories and storytelling in terms of power, knowledge, and difference (as was emphasized through the cultural turn) has opened new understandings of political, social, and cultural life, or risks abandoning crucial insights into the role of stories in geographical formations.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.028 |
| Scholarly communication | 0.009 | 0.020 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".