Bibliographic record
Abstract
We ground our discussion of phenomenology and literacy studies in a study of the Intergenerational Multimodal Literacy Programme. The programme brought together one kindergarten class from a school in Ontario, Canada with elder partners to engage in the creation and sharing of multimodal ensembles that featured art, singing and digital media. A study objective was to understand the constituents of curricula that can create opportunities for participant wellbeing by expanding their communication and identity options. Thirteen children (ages 3.8-5 years) and seven elder participants aided by the children’s teachers met once every two weeks over most of a school year for intergenerational sessions at a Rest Home near the school. The programme’s curriculum was premised on previous intergenerational multimodal curricula (e.g. Heydon 2013; Heydon and O’Neill 2014) but adapted by the school, Rest Home and research partners to respond to local needs and desires. Given that the programme was being run during school time, for instance, the curriculum had to address mandated literacy outcomes from a programmatic kindergarten curriculum (Ontario Ministry of Education 2006), and the partners had perceived a need to (re)connect community members in a rural setting that had recently experienced attrition and economic hardship. The partners reckoned that connections between people might be fostered and maintained even beyond the programme boundaries should participants expand their facility with various modes and media, most notably iPads. The programme thus purchased iPads for all of the participants who received support to use them both in and outside of the programme.
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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 | 0.029 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.015 | 0.068 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".