Bibliographic record
Abstract
Comic books are currently enjoying a resurgence in both public and scholarly interest. However, most of that scholarly focus has focused on how to use comics to engage with reluctant readers; educators are still struggling to recognize the medium as a “complex form of multimodal literacy” (Jacobs 2007). In both their complexity and their appeal, comic books gesture towards multiliteracy, a term that recognizes “the context of our culturally and linguistically diverse and increasingly globalised societies; to account for the multifarious cultures that interrelate and the plurality of texts that circulate” (New London Group 2000). Multimodal forms, in general, have very recently become of particular interest to instructors seeking new tactics to engage students within increasingly diverse classrooms. Lisa Leopold (2012) highlights widening research suggesting that learning styles can vary, among other things, according to culture. The results demonstrate that in order to appeal to students of all backgrounds, educators need to consider auditory, visual, and kinesthetic models or ‘texts’ for understanding the concepts and theories they hope to convey. Multimodality, herein, becomes important as the term that is used to describe the different texts of meaning, or rather the convergence of these texts, where different forms of communication work both together and in contrast in order to convey meaning. Comic books provide a unique opportunity to explore this convergence, given that they are hybrid texts themselves. By asking participants to think critically about how different modes of communication can be incorporated into a comic book, this workshop encourages educators to reconsider how the modes in which they communicate to their students can appeal to all learners.\nA wealth of recent scholarship suggests that important revisions need to be made to the traditional concept of literacy. While text slang, gifs, and emoticons provide us with dramatic examples of the organic formation of systems of communication, educational reform is still centered on linguistic learning. In order to free ourselves from the conventional view of literacy as a simple matter of words, it is important to consider the multiple systems of meaning – or multiliteracies – that we all navigate as functional members of society. As Jacobs (2007) argues, when we analyze comics as examples of multimodal literacy, we practice ‘critical engagement’ that can then be translated to other multimodal texts that we encounter in our daily lives. In this workshop, participants will first be challenged to utilize these multiple literacies in a group reading of a comic book. In the concluding half, participants will use this experience to investigate how incorporating elements of multimodal design into their lessons can be beneficial in appealing to the widest possible audience.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".