Reading Online News Media for Science Content: A Social Psychological Approach
Bibliographic record
Abstract
Reading multimodal (popularized) scientific texts is studied predominantly in terms of said-to-be-required technical decoding skills. In this article I suggest that there are other interesting approaches to studying the reading of multimodal (popularized) scientific texts, approaches that are grounded in social psychological concerns. These concerns include questions of what people read, how much they read, and the purposes and effects of reading. Here, I focus on (observable) cultural reading practices and the kind of semiotic (meaning-making) resources (popularized) scientific texts in online media make available for the practices of reading, including the way in which membership categories are used to link different aspects or parts of the text. A social psychological approach ought to be of interest to educators and educational psychologists, because, as part of ontogeny, members of society encounter reading first in their transactions with others, as an interpsychological phenomenon, before reading becomes an intrapsychological phenomenon. Important aspects of reading multimodal (popularized) scientific texts therefore can be found by studying sociocultural and cultural–historical practices and resources. Because “mind” is found in society, the development of higher order psychological processes, including reading, can be studied using methods more typically found in disciplines concerned with culture. In this article, I take inspirations from anthropological and ethnomethodological approaches to reading generally that are consistent with a cultural–historical approach and develop them for my study of the reading of online (popularized) scientific texts. My database includes all science texts that BBC published online between February 16 and March 31, 2007. I develop a framework for reading these texts from a cultural–historical (Vygotskian) practice perspective and provide exemplary analyses of reading such multimodal texts from the perspective of sociocultural and cultural–historical psychology.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".