Introduction: renewing the cultural politics of literacy education
Bibliographic record
Abstract
Literacy education is indeed at a historical crossroads. If we are to take educational policymakers, politicians and the media at their word, it is the same old great debate replayed over and over again: declining standards, loss of the literary canon, troubled and unruly students, irresponsible parents and overly permissive teachers. Bourdieu's trenchant vocabulary for talking about the systems of unequal and inequitable exchange in language and pedagogy, material and symbolic resources is more relevant than ever. From the French postwar system that he and Claire Kramsch (Ch. 3) experienced, to the worlds of inner-city students and migrants described here (Hill, Ch. 8; Grant and Wong, Ch. 9; Pahl, Ch. 10; Zacher, Ch. 13; Curry, Ch. 14), to Canadian workers described by Heller (Ch. 4), to those linguistic minorities subjugated by hegemonic monolingualism (Uhlmann, Ch. 6; Goldstein, Ch. 11) - the matter still is one of reproduction and counter-reproduction. As these chapters show, this is not a matter of an iron-cage structuralism of class, gender, and cultural reproduction. It is a complex system of generational and intergenerational exchanges of capital, the ongoing interplay of positions and position-taking in relation to the structuring fields of school, workplace, civic, and media cultures. Concurrently, the digitalization of text production has altered what counts as literacy in many ways, and the use of online representational forms is supplanting, augmenting, and appropriating print per se, altering its author/reader relations of exchange (Pahl, Ch. 10; Rowsell, Ch. 12; Dressman and Wilder, Ch. 7). This is to say nothing of the impact of cinema, video, and online texts on emergent claims about what might influence and reconstitute the canonical elements of the quality children's literature, academic study, and class-based literary taste. That is, the developmental sequences and systems of exchange that are hallmarks of the old literacy are being disrupted by convergence and crossover with the new literacies, even as schools and systems offer bare-bones policy and curricular attempts to incorporate new modes of representation and forms of life. The chapters that follow reveal openings for rethinking and moving beyond binary accounts of agency and reproduction in education. They exemplify how his concepts can be productively used to rethink literacy education in all its various manifestations as a field of practice. Adopting a strongly theorized Bourdieusian stance within our field is a strategic move. It is a continuing challenge to researchers and teachers to objectify and reflexively question the relations of class, exploitation, and inequality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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 teacher head, 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".