New families, new texts: An exploration of viewing, text, and schooling from the perspective of being an “other kind of family”. Language and Literacy: A Canadian Educational E-Journal
Bibliographic record
Abstract
…the nuclear family has, since the mid-twentieth century, been constructed as the natural social form in western epistemology and has informed much of the theorizing of the family in the West…. It has become a normative narrative against which others, and ourselves, have been measured. (Carrington, 2002, p. 17) My family is different. Not by any stretch of the imagination do we fit into the “normative narrative ” Carrington (2002) describes, nor do we fit into the “severely normal ” category described by former Alberta premier Ralph Klein, in reference to the typical Alberta family. I adopted my daughters as a single parent, as a third generation Canadian woman of mixed European and British ancestry, living in a Canadian province where relatively few singles adopt, a place that has been publicly known for being less tolerant of difference (Filax, 2002), and where, more recently, Bill 44 has been passed, allowing parents to have their children opt out (and be notified in advance) of any classroom discussions involving religion, sexual orientation, and sexuality, said to be supported by “severely normal Albertans ” (see CBC News, 2009).
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.035 | 0.053 |
| Scholarly communication | 0.026 | 0.020 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".