"From the darkness to the light": Memoirs of Blind Canadian veterans of the First and Second World Wars
Bibliographic record
Abstract
This article is a study of the memoirs of three Canadian ex-servicemen who were blinded during the First and Second World Wars. It inquires autobiographical accounts as a source to understand disability both at an individual and a social level. I argue that autobiographies, as they reflect the individual experience of disability, also reveal concepts and prejudices concerning disability that are inherent to a society at a specific time. The authors hence can either challenge or confirm persistent ideas about disability. This paper is organized in three parts. In the first I present the autobiographies this study is based on, and summarize their main features. In the second I focus on the way blindness impacts individual’s identity. I shall argue that the loss of sight is experienced as life-changing event, a death-rebirth process that deeply affects the veterans as well as their entourage. Blindness enhance hence a process of re-definition of the self which encompasses, on the one hand, blind individuals’ perception of their own ‘exceptionality’ and, on the other, their desire for normality and social integration. In the last section I analyze how the three writers address Canadian society in order to challenge the existing ideas and prejudices about the blind. I argue that they deliberately choose to use autobiographical narratives as a device to point out and challenge common preconceptions about blindness.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.060 | 0.034 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".