Oblicza wojny w kontekście teorii mediów Marshalla McLuhana
Bibliographic record
Abstract
Faces of war in the context of Marshall McLuhan's media theoryThe article shows how Marshall McLuhan’s media theory is used to analyze photographs taken with an iPhone. The reflections were inspired by the blog of the Canadian photographer Rita Leistner, who participated in the media project aimed at familiarizing American soldiers’ families and friends with everyday life of the military contingent in Afghanistan. Leistner, for the first time in her career, used a smartphone instead of professional photographic equipment. Her decision was motivated by the need to edit photographs easily and publish them quickly on the Internet. The result of her work was a blog, titled Looking for Marshall McLuhan in Afghanistan. To describe her photographs, Leistner uses selected concepts defined by McLuhan in the second half of the 20th century: probe, extension of man or figure-background dichotomy. In consequence, the technological face of war can be better understood by the viewers of the materials she prepared. Oblicza wojny w kontekście teorii mediów Marshalla McLuhanaW artykule przedstawiono sposób wykorzystania teorii mediów Marshalla McLuhana do analizy zdjęć wykonanych iPhone’em. Inspiracją do tych rozważań jest blog kanadyjskiej fotografki Rity Leistner, uczestniczki projektu medialnego, którego celem było zapoznanie rodzin i przyjaciół amerykańskich żołnierzy z codziennym życiem wojskowego kontyngentu w Afganistanie. Leistner, po raz pierwszy w karierze, używała smartfonu zamiast profesjonalnego sprzętu fotograficznego. Wynikało to z konieczności łatwego edytowania zdjęć i ich szybkiego umieszczania w internecie. Efektem tej pracy jest blog zatytułowany Looking for Marshall McLuhan in Afghanistan. Aby opisać swoje fotografie, Leistner użyła bowiem wybranych koncepcji sformułowanych przez kanadyjskiego myśliciela w drugiej połowie XX wieku: sondy, przedłużenia człowieka czy dychotomii figura/tło. Dzięki temu zabiegowi odbiorcy jej fotografii mogą lepiej zrozumieć technologiczny i medialny wymiar wojny.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".