Bibliographic record
Abstract
L THIS STUDY WE examine Percy Janes' use of non-standard Newfoundland dialect in House of Hate. All page references to the text are based on the edition published by McClelland and Stewart, Toronto, 1970. Janes was born in 1922, and published House of Hate, his second novel, when he was forty-eight. Growing up in Corner Brook, he spoke non-standard dialect at home, and 90% of the dialect in the novel goes back to that time (Janes, personal communication ). House of Hate spans the lives of four generations of one family •— that of Saul Stone — as remembered and interpreted by one of his sons, Juju, but concentrates essentially on two of those generations, namely Saul and his wife, Gertrude, on the one hand, and their six children, Henry, Hilda, Raymond, Crawford, Juju and Frederick, on the other. The narrator, Juju, describes how everyone within the Stone household suffers from the hatred that Saul seems to feel toward all around him, and the hostility toward himself that he generates in his own children. The novel is clearly autobiographical, and some have seen little more than autobiography in it. For instance, Cockburn remarked that House of Hate was little more than [thinly and unimaginatively] disguised autobiographical (115). It is certainly true that Janes has admitted to an autobiographical element in House of Hate, but he has at the same time been most insistent that the work transcends mere autobiography (Interview if). In view, no doubt, of comments such as Cockburn's, Margaret Laurence spelled out the differences between fact and fiction :
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".