Fragments in Connection and Algorithmic Rule: Encoding the Urban Image in Motion
Bibliographic record
Abstract
Abstract Art, architecture, cinematography, and media as urban images in motion concerning digitalization are discussed based on the images of a result, success, conquest, and projection that search for the spectacular, concrete, and imagined achievements related to the transformations of visual culture. Media, information, and communication technologies offering experiences to individuals in their urban reality construction choices are discussed, faced with the image's paradoxes in its figurative and abstract sense. Therefore, media presence is discussed based on the algorithmic rule, which directs society towards a significant paradigm change concerning new spaces and times for concrete experiences. The reflection on art, architecture, cinematography, and media delimits this interdisciplinary analysis in human sciences. The focus is the culture in its transformation related to urban visual and digital aspects based on the theories of perception and aesthetics about urban assemblages. Therefore, concrete and imagined urban experiences are analyzed by assemblages and montages of fragmented images originated and influenced by cinematographic and animation languages to construct moving images. This study will also address an understanding in information and communication sciences about virtual realities and effects generated by the world wide web through hypermedia and multimedia, which impact social behavior. However, what condition would the change of architecture be according to the configuration of the digital image? This question seeks answers in information sciences through the digital image by specific codification to optimize time-space versus the human perception and visual system. Finally, an interdisciplinary approach is proposed to explore the possibility that perception remains a hypothesis for the meaning of contemporary visual culture in its values and effects related to the fragments in connection and algorithmic rule in the imagined and concrete realizations of the urban image in motion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".