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Record W2561589228 · doi:10.4000/ideas.1677

Interview with Louie Palu, Canadian award-winning photojournalist who examined communities in the Hard Rock Mining Belt, one of the richest mining regions in the world located in Northwestern Ontario and Northeastern Quebec

2016· article· en· W2561589228 on OpenAlexaboutno aff
Lucie Genay

Bibliographic record

VenueIdeAs · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
FundersHarry Ransom Center, University of Texas, AustinUniversity of Texas at AustinNorthwestern UniversityJohn Simon Guggenheim Memorial Foundation
KeywordsExhibitionFilm directorPoliticsPolitical scienceLibrary scienceVisual artsArt historyHistoryArtLawMovie theater

Abstract

fetched live from OpenAlex

Louie Palu is a documentary photographer and filmmaker whose work has appeared in festivals, publications, and exhibitions internationally, including the 2012-2013 landmark exhibition “War/Photography: Images of Armed Conflict and Its Aftermath.” His work examines social political issues such as human rights, conflict and poverty. In addition to being the recipient of numerous awards including a Pulitzer Center on Crisis Reporting Grant, he is a 2016 John Simon Guggenheim Foundation Fellow an...

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)0.002
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: none
Teacher disagreement score0.198
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0240.005
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.072
GPT teacher head0.241
Teacher spread0.169 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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