Bibliographic record
Abstract
This special issue of Boyhood Studies takes two terms—boys and storytelling—and positions them alongside one another. In some ways, we take seriously Charles Dickens’s oft-quoted notion that “A boy’s story is the best that is ever told.” What does it mean to take the stories of boys and boys’ stories seriously? Are they really among the “best that [are] ever told”? In the space of education, and with declining literacy rates among boys, what does it mean to study storytelling? Or, what might it mean, to borrow a phrase from Carol Mavor (2008), to “read boyishly”? In this special issue, we hoped to bring together scholars working on the relationship between boys and storytelling, to consider the kinds of stories that boys are told, and to also consider the stories that they are not told. Our goal was to consider the importance of storytelling in boys’ lives as well as the importance of the storytelling of boys’ lives. That is, we were interested in boys as both real and embodied, as well as in the fictional boys that populate the literary universe. The issue presented here brings together a host of perspectives that all work to explore and expand the literary and cultural study of boys and storytelling.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".