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Record W2059759980 · doi:10.1353/par.0.0000

On Common Knowledge and <i>Ad Populum</i>: Acceptance as Grounds for Acceptability

2008· article· en· W2059759980 on OpenAlexaff
David Godden

Bibliographic record

VenuePhilosophy and Rhetoric · 2008
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsArgumentation theoryArgument (complex analysis)Rhetorical questionNothingEpistemologyPersuasionContext (archaeology)DialogicSet (abstract data type)Computer sciencePsychologyPhilosophySocial psychologyLinguistics

Abstract

fetched live from OpenAlex

On Common Knowledge and Ad Populum:Acceptance as Grounds for Acceptability David M. Godden Starting points for argumentation All reasoning, including the reasoning used in argument, has to start from somewhere. Although it may be possible, in principle, to offer support for every claim, in any particular case this strategy cannot be used without hopeless regress. Thus, not every claim used in reasoning can owe its acceptability to some set of reasons offered in its support. Instead, in the context of any given argument or piece of reasoning, some claims must be accepted—if only as starting places—on some other basis. These claims can be called the basic premises of an argument.1 Dialogic approaches to argumentation typically take as the starting place of argumentation the discussants' shared commitments. Alternately, rhetorical approaches standardly take as the starting place of argumentation the audience's existing commitment set or, more broadly, whatever an audience is willing to accept. With each approach the idea seems to be that the effectiveness of persuasion depends on the commitment of the audience to the starting points of argumentation. In a dialogic context, if there are no points of agreement between a proponent and opponent, there is nothing for arguers to "take hold of " when designing and deploying their arguments and no space in which argumentation can take place. In reasoning more generally, if no claims are initially admitted, there is nothing from [End Page 101] which inferences can be drawn, for inference can only generate claims on the basis of other claims. Further, there may even be nothing with which to draw inferences, for if no inferential rules are initially accepted, there will be no inferential moves that can be made even given some initial data set. In these approaches the fact of acceptance (or agreement) seems to give a prima facie acceptability to a set of claims (which I will call an initial commitment set) used as a starting place for argumentation. As a starting place for argumentation, an initial commitment set can include both good and bad information. More generally, we tend to hold that most of our commitments are fallible—they are subject to defeat as refuting evidence comes to light. As such, some claims in an initial commitment set might be unacceptable according to any relevant standard of acceptance. The hope is that the projects of inquiry, argumentation, critical examination, and rational assessment will help sort things out by weeding out the bad claims in the initial commitment set. So, that some claim is accepted by an arguer is a reason for it to be a starting place in argumentation, although it is not on its own a reason (even a prima facie reason) for its acceptability. Rather, the acceptability of a claim is determined by how well it survives the process of argumentation, not where it stands at the beginning. In this article I explore the role acceptance can play in establishing the acceptability of a claim by examining the relationship between appeals to common knowledge and appeals to popular opinion. Typically, that a claim is common knowledge is taken as grounds for its acceptability, whereas appeals to popular opinion are seen as fallacious attempts to support a claim. Against this I argue that appeals to common knowledge generally provide no better evidence for a claim than appeals to popular opinion and, as such, that appeals to common knowledge ought to be just as successful—or unsuccessful—as appeals ad populum. I begin by describing a standard account of appeals to common knowledge and popular opinion that should be familiar to anyone who has taught or studied reasoning skills. I proceed to set out an alternative to this standard view (largely due to Douglas Walton) on which some appeals to popularity can provide defeasible yet presumptive support to a claim sufficient to shift a burden of proof on the balance of considerations. In general, I hold that the standard account is correct and that where ad populum appeals succeed in providing good reasons, they do so because they have been reconstructed as having another argument form that introduces independent reasons for accepting the conclusion. Each of these accounts helps to...

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)0.017
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0090.060
Scholarly communication0.0170.027
Open science0.0030.008
Research integrity0.0120.015
Insufficient payload (model declined to judge)0.0120.003

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 head0.039
GPT teacher head0.280
Teacher spread0.241 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
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

Citations26
Published2008
Admission routes1
Has abstractyes

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