Bibliographic record
Abstract
MIGRATION IMAGES AS A READING This study aims to examine how the phenomenon of migration, having significant causes and consequences throughout the history, is expressed by means of photography and read the phenomenon of immigration through images. Especially in the present day, the phenomenon of migration which we have witnessed its bad causes and consequences on behalf of humanity has been the subject of research and discussion in many fields. Today, many artists are influenced by the phenomenon of migration. They transform this human tragedy brought by migration into an artistic means of expression and articulate their thoughts and questions through art. One of these art fields is photography which has a universal power for expression. A photograph does not only documents or records the phenomenon of migration. It also carries out an important function by opening up the phenomenon of migration for discussion. Keywords: Migration, Photography, Migrant, Refugee, Document Oz Bu calismanin amaci, tarihin her doneminde onemli nedenleri ve sonuclari olan goc olgusunu fotograflar araciligiyla nasil ifade buldugunu arastirarak, goc olgusunu fotograflar uzerinden okumaktir. Ozellikle gunumuzde, insanlik adina kotu sebep ve sonuclarina yakindan taniklik ettigimiz goc olgusu bircok alanda arastirma ve tartisma konusu olmustur. Bugun pek cok sanatci, goc olgusundan etkilenmis ve gocun beraberinde getirdigi insanlik dramini sanatsal bir ifade aracina donusturerek, dusuncelerini ve sorgulamalarini sanat araciligiyla yapmaktadirlar. Bu sanat alanlarindan biri de evrensel bir anlatim gucune sahip fotograftir. Fotograf goc olgusunu sadece belgelemekle yetinmez. Goc olgusunu tartismaya acarak onemli bir islevi de yerine getirir. Anahtar terimler: Goc, Fotograf, Gocmen, Multeci, Belge KAYNAKCA Barthes, R. (2017).Goruntnun Retorigi Sanat ve Muzik, YKY yayinlari,Istanbul. Berger, J. (2015). Bir fotografi anlamak . Metis Yayinlari. Deleuze, G. ( 2004) Sinema 1 Hareket-Imge, Norgunk yayinlari, Cev: Ozdemir, S. Istanbul. Jelekainen, E. (2015). Immigrant Artists’ Intercultural Identity Formation And Development Process Through Art Making, Master’s Thesis, University of Jyvaskyla. Kagan, M. (1993). Estetik ve Sanat Dersleri, Cev: Calislar.A. Imge Kitabevi. Ankara Ziss, A. (2009). Gercekligi Sanatsal Ozumsemenin Bilimi, ESTETIK, 2. Baski, Cev: Sahan, Y. Istanbul. Yararlanilan internet kaynaklari: https://www.haberturk.com/kultur-sanat/haber/1129329-afgan-kizini-goren-gozden-suriyeli-aylan-bebek-yorumu# 20.11.2018 Tarihinde yararlanilmistir. GORSELLER Fotograf 1- 2: Mubadele donemine ait bir fotograf: https://www.google.com.tr/search?q=eski+m%C3%BCbadele+d%C3%B6nemine+ait+foto%C4%9Fraflar&tbm=isch&tbo=u&source=univ&sa=X&ved=2ahUKEwjypMDvk_zeAhUwqIsKHeOpAE4QsAR6BAgEEAE&biw=1280&bih=585#imgrc=IPcCAKNgxBhEjM:&spf=1543582227117 internet adresinden 26.11.2018 tarihinde alinmistir. Fotograf 3: Nilufer Demir,Aylan Kurdi Bebek, (https://www.haberturk.com) 20.11.2018 Tarihinde indirilmistir. Fotograf 4: https://tr.sputniknews.com/avrupa/201602011020574567-aylan-aiweiwei-yunanistan/22.11.2018 Tarihinde indirilmistir. Fotograf 5: Pekka Jylha artwork, sculptor, https://en.prothomalo.com/photo/gallery/97011/TODAY-IN-PICTURES-04-March-2016, A sculpture created by Finnish artist Pekka Jylha portraying drowned Syrian refugee Alan Kurdi, is seen on display at the Helsinki Contemporary gallery in Helsinki, Finland March 3, 2016. Photo: Reuters 25.11.2018 Tarihinde indirilmistir. Fotograf 6: https://www.dailymail.co.uk/news/article-3227703/Thirty-people-recreate-death-Alyan-Kurdi-laying-sand-Moroccan-beach-dressed-clothes-drowned-Syrian-boy.html 28.11.2018 Tarihinde indirilmistir.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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.
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".