Language, Literacy and Mind: The Literacy Hypothesis Lenguaje, Literacidad y Mente: La Hipótesis de la Literacidad
Bibliographic record
Abstract
Literacy is important not only as a means of access to new information and as an extension of memory. Rather, it is argued that writing is a means to the awareness of the implicit properties of language. This awareness is expressed through new concepts for referring to what is said, what is meant by it, what it implies, of what it is composed, and the like. Writing achieves this effect through distancing the thoughts of the writer from the fixed, objective form it takes when written down. The effect on the reader, correspondingly, is equally distanced from the writer with the result that reading is less like hearing a speaker that like over-hearing. I describe this effect by saying that writing puts language within quotation marks. La literacidad no solamente es importante como un medio para acceder a nueva información y como extensión de la memoria. Se propone, en cambio, que la escritura es un medio para tomar conciencia de las propiedades implícitas del lenguaje. Esta toma de conciencia se expresa a través de nuevos conceptos para referirse a lo que se dice, su significado, sus implicancias, los elementos que lo componen y otros aspectos similares. La escritura logra este efecto al distanciar los pensamientos del escritor de la forma fija y objetiva que adquieren al ser escritos. De manera equivalente, el lector vive un proceso de distanciamiento similar al del escritor, con el efecto que leer se parece menos a escuchar directamente a un hablante que a escucharlo sin que este se dé cuenta. Describo estos efectos señalando que la escritura pone al lenguaje entre comillas.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".