Notice bibliographique
Résumé
Hailing Distance:On Citation and the Pandemic Sarah Banting (bio) I wrote the first draft of this piece during the very June, 2020, days when, instead of being at Congress, I was alone in my bedroom on a quiet Calgary crescent. Feeling the loss of the conference, I seized on the chance to write. Doesn't it hurt, not to have been heard by colleagues this spring, not to have heard others speak about their work? I was to give a paper in London about scholarly citation in literature studies. And I was looking forward to hearing our colleagues' reflections about citation at the accute Committee for Professional Concerns panel discussion on the topic; I anticipated being influenced, affected—not to say infected—by their ideas. What I have to say here is inflected, like just everything these days, by the novel coronavirus, but I am writing about a more enduring phenomenon. If my thoughts here make an impact on your practice, I hope their effect outlasts—and is much gentler than—this moment. I also hope that, if you ever have occasion to cite me, I will recognize my words in your citation. Here it is: how we cite, in this discipline, looks rather like how we must socialize during this pandemic. We give perfunctory and amiable shout-outs, in footnotes, to fellow scholars' work; I holler to my neighbours across an acceptable divide of lawn. We enjoy—I think we do enjoy—the [End Page 17] lonely freedoms of scholarship in the "diffuse" intellectual space of a discipline like ours (MacDonald); meanwhile, the diffuse sprawl of our field of study resembles the de-densified geography of a city, a nation, a planet, when people just stay home. I don't mean that our citations are fearful, meant to ward off contagion; usually they are open-hearted and neighbourly. But they testify to the solitude of our work. I'm going to give you just the briefest of glimpses, here, of what analysts say about our citations and of what I find when I analyze them myself. These glimpses may begin to illustrate that, in citation as in a pandemic, we scholars in literary studies have few close companions—just a handful of chosen ones whose presence we fully register in our work, whom we identify with or define ourselves against, with whom we dutifully spend time. We cite most of our scholarly neighbours from a distance, respectfully hailing work that approaches ours but never quite comes into contact with it. The moments where we represent others' work in our own make for intertextual threads of contact between our projects, but most of those threads are slender and far-flung. Chalk it up to the exceptional loneliness of this moment, but I will conclude this piece with a plea for a closer citational embrace. Home offices When Writing in the Disciplines (wid) scholars analyze literary scholarship, one finding is that this discipline is decidedly "diffuse" (MacDonald 22): by comparison to the "compact" social sciences, in which many scholars are studying tightly-related, collectively defined problems, and in which each researcher contributes directly to the collective construction of knowledge, literature scholars do not build directly on each other's work. Rather, we set out to explore new territory, to generate not only original findings but original questions; according to Katja Thieme, we describe even our analytical methods as "not easily shared with other projects" (105). Our scholarly citations illustrate the dispersion of our work across what seems to be an endlessly expansive field. Although we share interest in texts, in regions and histories, in theories and advocacies, in the keywords of our discipline, we approach those shared interests in solitary ways. Studies of our citations have found that even when we join a long tradition of scholarly commentary on a canonical text, we do not arrive at that tradition as if at an established, shared edifice (Hyland; Hellqvist). Rather, we selectively build unique contexts for our individual work. When academic librarians David S. Nolan and Hillary A.H. Richardson went looking for a set of landmark scholarly works that would form a "core collection" [End Page 18] (453) for a...
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,053 | 0,233 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,013 | 0,015 |
| Études des sciences et des technologies | 0,020 | 0,055 |
| Communication savante | 0,039 | 0,062 |
| Science ouverte | 0,005 | 0,020 |
| Intégrité de la recherche | 0,022 | 0,022 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,004 |
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 source (Gemma direct ou Codex distillé), 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 ».