Notice bibliographique
Résumé
Valuing the Devalued, or Dirty Apprehension Travis V. Mason (bio) The first part of my title comes from a poem by Ken Babstock, who wrote “Thingymajig” (17), from his second collection, Days Into Flatspin (2001), “in response to a question” posed by Saturday Night magazine (Babstock 81). Seeking ideas for a millennial issue, the magazine asked readers “What idea, trend, or technology should make an impact on our lives in the next century” (81)? Babstock’s poetic response, as his title indicates, evokes “an imagined gadget,” “a custom- / welded foraging tool” that would enable its user to navigate “the leagues of cast / offs, discards, used-ups, // and general rot that pour[s] daily into urban Dumpsters.” The dirt and detritus of everyday life in the global north become targets for city dwellers looking to make ends meet, if not entirely to counter the entropy of late-capitalist consumerism. Under this consumerist rubric, the act of losing is less an art, as Elizabeth Bishop would have it, and more a logical extension of planned obsolescence and over-production. Key in this millennial relation between people and the dirt we produce is a revaluation of that dirt. The poem ends by reconsidering Bishop’s claim that “the art of losing isn’t hard to master”—“Finding what it is we lost, want, or most need’s a tougher / nut, but valuing the devalued might / get me it faster.” What is it, precisely, that has been lost besides bric-a-brac accumulated [End Page 14] over time? And what might the finding imply about how we, as humanists, understand and write about the world? Perhaps what has been lost is an earth free of the dirt with which humans have polluted it? In “Dirt Theory and Material Ecocriticism,” Heather Sullivan invokes a nostalgic view of nature as “clean” and “pure” (515), which she rightly claims ecocritics and environmentalists have privileged. Beyond environmentally concerned discourse, however, nature is often viewed as dirty. Humanity is more often seen as clean and right; culture and (human) intelligence occupy the bulk of humanist concerns. Ecocriticism hasn’t gained widespread acceptance in the Canadian academy—I can think of maybe two job advertisements since 2006 that even mentioned ecocriticism. Perhaps this is because, unlike those ecocritics to whom Sullivan refers (predominantly American), ecocritics like me tend not to reify untouched nature, also known as wilderness. Don McKay’s essay “Baler Twine: Thoughts on Ravens, Home, and Nature Poetry” was first published in The Fiddlehead in 1993; it has been reprinted numerous times since. A foundational essay, it is not one, I suspect, that is as widely read amongst Canadian literary scholars as it ought to be. The essay contains a definition of wilderness, oft-quoted by ecocritics but again, I suspect, not well known by many others. “By ‘wilderness,’ ” McKay writes, “I want to mean not just a set of endangered spaces, but the capacity of all things to elude the mind’s appropriations” (Vis 21). The tools we have made—from shoelaces to computers—retain “a vestige of wilderness,” the possibility of breaking down the walls of domestication (21). Wilderness, in other words, will find us, not the other way around. Babstock’s urban dirtscape invites environmentally minded questions perhaps even more than lyrical paeans to an imagined nature unaffected by human presence. I don’t think his poem expresses a longing for wilderness as endangered space. What I want to take from “Thingymajig” is the possibility of digging through the dirt and detritus as a way to move forward, perhaps literally—freeganism is a thing—but also intellectually. Actually, as scholars conducting research and publishing our engagement with others’ arguments, we often do practice an intellectual form of reaching into the detritus and piecing bits together: maybe we just don’t acknowledge our work as such. Maybe we should. Or maybe we should get even dirtier in the way we conduct ourselves as scholars—maybe the bits and pieces we find in past ideas aren’t dirty enough because we tend to seek out works from similar fields. Despite institutional calls for interdisciplinary work, dilettante remains a dirty word in academia. And I have never...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».