Photographic Encounters with (In)visible Mothers in Roland Barthes’ Camera Lucida, W. G. Sebald’s Austerlitz and Erri de Luca’s Non ora, Non qui
Bibliographic record
Abstract
This article deals with three literary texts by Roland Barthes, W. G. Sebald and Erri De Luca, linked with each other thanks to the employment of photography in relation to the image of the mother. Yet, the ways in which each author negotiates with the mother-son photographic encounter are diverse: while in Barthes the photograph of his mother is substituted by the one of another woman, Nadar’s mother, in Sebald the photograph is physically printed on the page and interspersed within the literary narration; finally, in De Luca the photograph is depicted only verbally. On the one hand, photography seems to be the right medium to use in order for the process of recollection to be fulfilled; on the other hand, its employment problematizes some of the medium’s characteristics. Indexicality, materiality, and the relationship that the act of viewing establishes between the self and the other, as in such encounters, for instance, “the image becomes a subject and the subject becomes an image” (Cadava 2009, 9), are indeed put under scrutiny. The distance between the narrators and their mothers is not uniquely temporal (the former are always older than the latter, who are mainly framed as young girls, thus deprived of their motherhood, and deceased at the moment of the narrators’ recollection) but also spatial. Photography, and its usage within verbal narrations, creates in fact a separation—both ideological and material—between the space of the viewer and that of the viewed. In sum, the comparison among these texts promotes a reconsideration of the ontology of the photographic medium, in particular of its presence/absence dichotomy, as “a photograph is always invisible” (Barthes 1980, 18), and a re-contextualization of the space/time units, among other issues.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".