Understanding literature through popular culture: a case study of senior high school students' evolving responses to Québec literature
Bibliographic record
Abstract
Francophone Quebec, as a minority culture in North America, needs to pay attention to and celebrate not only what makes it different within the North American context, but also what it shares. Literature, as a branch of the arts, takes the pulse of the society that it represents. In this regard, American novelist Richard Ford (2011) states that literature "realigns conventional wisdom" all the while improving its literacy levels. Apart from functioning as an effective instrument of education (Carroll, 2002), literature is also the means through which language skills are most often taught in Quebec's French classes. Regrettably, the province of Quebec has more people with low literacy than the national average, which results in a weak foundation for future learning, including formal learning at the post-secondary level. Research points to students' loss of interest in French classes as a common cause for this alarming phenomenon. In addition to this issue, only approximately half the Quebec student population over 16 years of age (52%) have a literacy level at or above the estimated level for living efficiently (O'Sullivan et al., 2009). This is a serious educational and social challenge that needs to be addressed. In an effort to reduce the weak literacy rate of students, I suggest an alternative teaching of Wajdi Mouawad's Quebec play Incendies in three different secondary 5 classes. I charted patterns of meaning-making responses that provide an understanding of directions a teacher might take to increase interest in reading, specifically within the francophone community. The patterns of responses are meant to help educators by providing them with student responses where it seems advisable. Another objective of this study is to adopt appropriate methods to reinforce an interest in Francophone Quebec literature and develop a further interest in reading.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.033 | 0.013 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| 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".