Social justice for young readers: advocating for access, choice and time to read
Bibliographic record
Abstract
Abstract In a socially just world, everyone would have an equal chance to become an enthusiastic reader. This article presents a detailed ‘asset map’ of a successful reading life and investigates three necessary components for creating readers: access, choice and time to read. Access to books, the chance and the requisite knowledge to choose reading materials of genuine interest, and time to read and thus to develop reading stamina are all vital to reading success. Although they sound simple enough to supply, access, choice and time to read are all currently under attack. The provision of public and school libraries is threatened in many countries; in the absence of easy access to libraries, young people consequently have much less opportunity to practice book selection in a low‐stakes environment; and many classroom activities ironically limit reading time in favour of exercises and seatwork. Those working for socially just literacy options and affordances must decide on the most productive use of energy and resources to pursue a more level playing field; access, choice and time to read are necessary conditions of reading success.
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 | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.023 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".