MétaCan
Menu
Back to cohort
Record W1553211702

Snapshots from the South African War: The F.C. Cantrill Photograph Collection at the Canadian War Museum

2000· article· en· W1553211702 on OpenAlexaffabout
Brendan McCoy

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsVisual artsArt historyHistoryArt
DOInot available

Abstract

fetched live from OpenAlex

The Canadian War Museum’s (CWM’s) Photographic Archives contains over 600 photograph collections or fonds. These include over 17,000 individual photographs, some with their original negatives, and more than 250 photo albums. This collection has been acquired from private sources, with the photographs for the most part representing the personal documentation of Canada’s military history by the participants. These have been brought together as part of the CWM’s mandate to collect, preserve and make available for research and exhibition the artifacts of the Canadian military experience. The collection of Frederick Charles Cantrill who served in the South African Constabulary from 1901 to 1903 is one of these.1 Larger than some, much smaller than others, this collection is typical of the personal photography undertaken by soldiers throughout the century. It is discussed here both as part of the CWM’s ongoing commemoration of Canadian participation in the South African War, and as an illustration of the interesting informal nature of many of the CWM’s photographic holdings. The article will examine Cantrill’s own story, the developments in photography that made his collection possible and, in the captions, assess what the photographs add to our understanding of Canadians in the South African War.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0210.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.002

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.

Opus teacher head0.011
GPT teacher head0.185
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueScholars Commons (Wilfrid Laurier University)Same topicCanadian Identity and HistoryFrench-language works237,207