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Record W7060871023

Pictorial Communication

2021· dissertation· en· W7060871023 on OpenAlexfundno aff

Bibliographic record

VenueCUNY Academic Works (City University of New York) · 2021
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDepictionTask (project management)Connection (principal bundle)Visual communicationConjunction (astronomy)Interpretation (philosophy)Action (physics)Feature (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

The primary goal of my dissertation is to reconcile an anti-intentionalist account of depiction with an intentionalist account of pictorial communication. I begin by providing an account of depiction and then provide an account of communication and, specifically, pictorial communication. Accordingly, I begin by defining depiction, and reject what I call the ``ambiguity view'' which holds that terms like ``depiction'' and ``representation'' are ambiguous. I argue that P depicts O if the design of P visibly manifests O. This definition of depiction sets up the central task for a theory of depiction: to explain how it is possible for a marked surface to facilitate a visual experience as of O. To answer this question I defer, partially, to Dominic Lopes's recognition view. I agree with his claim that a picture, P, depicts something, O, if and only if P is able to trigger the capacity for a suitable perceiver in suitable conditions to recognize an O by its appearance. However, I don’t adopt his second condition which requires a causal connection between O and P. Additionally, I argue that recognition alone does not provide an adequate theory of depiction because it does not explain the visual experience characteristic of engagement with pictures. I suggest that the recognition view should be supplemented by a view that explains visual experience. Specifically, I argue that a picture acts as a functional surrogate for O. The design features ground, sustain and constrain visual experience of O. I argue that by grounding and sustaining a visual experience as of O, while not itself being O, a picture’s design effects an illusion. In the second chapter I discuss communication which I define as an intentional and purposeful activity involving at least two participants: U and A. It is necessarily mediated by a public utterance—symbol, signal, sense bearing sign—that U produces. Communication succeeds when A understands what U means—more precisely what U means by what U says. Based on this Gricean account I arrive at three theses that I expect to inform my discussion of pictorial communication. These are: (a) when a picture is used as a vehicle of communication, its meaning and the goal of pictorial interpretation are determined by the picture maker’s intentions; (b) a picture can bear nonnatural meaning so interpreting it correctly would require recognizing this; and (c) a picture may implicate, or suggest, some meaning over and above its ``literal'' meaning. In the second chapter I develop these three theses. The first two are closely related. Insofar as a picture is used as a vehicle of communication it bears nonnatural meaning. A picture’s nonnatural meaning is essentially the embodiment of picture maker’s meaning. So the goal of pictorial interpretation (when the goal is communication) is to identify the picture maker’s meaning. With respect to the third thesis, I consider Catherine Abell’s account of pictorial implicature and reject it on the grounds that it fails to distinguish between what a picture implicates and what it depicts and she holds that the latter determines the former. I distinguish between two kinds of implicature: those that rely on symbolic cues and those that rely on perceptual cues (plus the reality principle and Gricean maxims). A picture’s content furnishes these cues. Pictorial implicatures are generated by depictive content. Nevertheless, what a picture implicates is part of maker’s meaning. Finally, I consider the objections to the claim that communication, as I have described it, is a legitimate goal of pictorial interpretation.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0070.010
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0410.005

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 head0.035
GPT teacher head0.290
Teacher spread0.256 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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