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Record W4413911620 · doi:10.32920/ifmj.v5i1-2.2442

Senses and Sense-ability

2025· article· en· W4413911620 on OpenAlexvenueno aff

Bibliographic record

VenueInteractive Film and Media Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSense (electronics)CommunicationPsychologyEngineering

Abstract

fetched live from OpenAlex

Resonance, the conference’s central theme, refers to our ability to form deep, meaningful connections that provoke thoughts, evoke emotions, and stimulate the senses through personal images and memories, often drawing on an individual or community’s lived experiences” (“Call For Proposals | Interactive Film & Media Journal”). Communication of these individual and community experiences requires a medium, usually a common language. One common language that transcends linguistic, socio-political, and even species-specific boundaries is the language of care. This paper explores the role care has in the process of resonance formation and demonstrates that care is a language and a medium with universal elements. It further discusses how this repositioning of care as a medium can help us use resonance in a socially responsible manner with regard to solidarity and collective formation. Even when communicating through personal images and memories, the significance of these moments is not only derived from their visual or verbal representations but also the emotional resonance they create. To gain further insights into this phenomenon, this paper establishes the theoretical framework by intersecting linguistics, education, and media studies to establish that care can be viewed as a language and medium, which makes it central to the discussion of resonance. In addition, feminist studies and ethics of care will be central to further exploration of resonance to examine the latter’s role with regard to creating solidarity and collective. These frameworks are then applied to an analysis of interspecies relationships with companion animals to disentangle the verbal competent from the complex structure of care communication to explore the relevance of care as a language in the context of resonance and meaning-making. This discussion further references materials relating to animal studies. Insights gained from interspecies relationships with companion animals, which rely predominantly on nonverbal communications of care, demonstrate how the interpersonal nature of this type of communication foregrounds practices of deep listening/observation, interpretation, and simulation. Resonance remains integral to these relationships in the absence of verbal communication. This disentanglement of the verbal component from care language provides key findings that are then used to investigate the non-verbal elements of resonance in human-to-human relationships. The findings from the analysis of interspecies relationships aids the analysis of human-to-human relationships, where examples of communication between speakers of different languages and the same languages are scrutinized to examine the role of care as a non-verbal language and its relevance to resonance. The discussion furthermore explores this role within the contexts of creating solidarity and collectives. Using these analyses, the paper argues that the language of care in its interpersonal form is integral to creating solidarities and collectives based on a sense of belonging that derives from the resonance care as a language establishes. Key Hypotheses: Considering care as a language and a medium repositions it as a form of communication rather than an activity. Disentangling verbal and non-verbal communication of care allows for a more in-depth understanding of resonance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.340
Teacher spread0.323 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

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