Bibliographic record
Abstract
Howard Akler, The City Man. Toronto: Coach House Books, 2005. 154pp. $14.95 Because Chicago Review is a serious publication, given to sober criticism and averse to fawning blurbs, I feel bound to reveal straight away that The City Man contains a simile that strains my objectivity. Toronto, 1934: pickpocket Mona Kantor, trailing a mark through Union Station, watches back of suckers head and finds His yarmulke askew like a large lazy eye. Consider yourself warned. In games of word association, utterance of word is answered inevitably, instantaneously, with cry Rhythm! This claim does not seem so far-fetched in world of The City Man, a spare, episodic first novel from Howard Akler. Pickpockets, hustlers, touts, and grifters ease through Toronto's Depression-era streets, their speech as deft as their fingers and feet. Good timing here is not just a tool for conning bateses, pinching pokes, scoring pits. It's a sign of a sensibility, a kind of knowingness. Characters with rhythm of movement or language see and sense things to which other Torontonians, lazy-eyed suckers all, are oblivious. In manner of its characters' clipped but rhythmic speech, Alder's third-person narration taps out an easy patter, often in imagistic sentence fragments. Parts of speech are rationed in downtrodden city, forcing readers to fill in blanks-pronouns, verbs, articles-the way impoverished citizens patch their suits. Mona, our grifter heroine, has most preternaturally perfect timing in novel. She is a stall: that half of a pickpocketing duo responsible for manoeuvering mark into position through imperceptible nudging and blocking. Once victim has been set up, stalled for subtlest instant, cannon moves in to pull touch, reef an easy kick. (Provided no one crumbs play.) The argot and choreography of pickpocket or the whiz do not penetrate dull senses of upright citizens; as one grifter puts it to a reporter, We can kibbitz right there in front of sucker and he don't even Eli Morenz is Toronto Star's city man. In addition to his ear for puns, Eli has a feel for pace of an interview that's as keen as Mona's sense of whiz. He extracts information with deft nonchalance-never rumbles a bates. Eli is only Torontonian who experiences Mona's genius as anything other than an inexplicably empty pocket. Making strategic use of an incriminating photo of her taken by a Star photographer, Eli induces Mona to instruct him in art of grift. In their first class, she trails him around his tiny apartment, picking his delighted pocket again and again. (Eli feels nothing but her eyes.) In a subsequent session, she forks over grifter lexicon: Bang a souper? Steal a pocket-watch. Good, says Mona. Keister kick? Uh. Hip pocket. The dipsy? A warrant. Centre britch? Eli flushes. Uh, he says. Come on come on. Well, space between left britch and right britch. The cock, says Mona. Right. Cock. You're catching on. How about raust? Um, says Eli. Mona jabs his hand with lit end of her cigarette. Ow! What was that for? An example, says Mona. A raust is misdirection. Her lessons-the less interesting ones, anyway-he publishes in Star, giving readers/suckers a glimpse of (under)world they fail to notice. As quoted passage suggests, intersection of economies in which Mona and Eli respectively specialize-of cash and information-is flirtatious. Eli's pocket is happily plundered; Mona hands over her secrets under most flattering duress. It doesn't take long for a third economy to spring up: Her hand steals away from small of his back. Lolls along thigh. Fingers his asshole. Uh, says Eli. That's not my pocket, you know. …
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.165 | 0.087 |
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".