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Record W3143684518 · doi:10.1353/esc.2018.0026

Hailing Distance: On Citation and the Pandemic

2018· article· en· W3143684518 on OpenAlexvenueaboutno aff
Sarah Banting

Bibliographic record

VenueEnglish studies in Canada · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCitationScholarshipMedia studiesWonderFeelingSociologyHistoryLawPsychologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

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...

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 imitation

Not 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.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.233
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.279

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.233
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0130.015
Science and technology studies0.0200.055
Scholarly communication0.0390.062
Open science0.0050.020
Research integrity0.0220.022
Insufficient payload (model declined to judge)0.0150.004

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.

Opus teacher head0.053
GPT teacher head0.342
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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