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Record W2123276999 · doi:10.1145/1940761.1940841

Multi-lifespan information system design

2011· article· en· W2123276999 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the 2011 iConference · 2011
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsGrassrootsTribunalWork (physics)Set (abstract data type)Field (mathematics)Computer scienceReuseInformation systemPublic relationsSociologyKnowledge managementData sciencePolitical scienceEngineering

Abstract

fetched live from OpenAlex

In this paper we report on our research and design efforts to provide Rwandans with access to and reuse of video interviews discussing the failures and successes of the United Nations International Criminal Tribunal for Rwanda (UN-ICTR). We describe our general approach and report on three case studies with diverse sectors of Rwandan society: governmental information centres, youth clubs, and a grassroots organization working with victims of sexual violence. Our work includes the development and application of five indicators to assess the success and limitations of our approach: diverse stakeholders; diverse uses; on-going use; cultural, linguistic and geographic reach; and Rwandan initiative. This work makes three important contributions: first, it offers the information field a design approach for use in post-conflict situations; second, it provides near-term evaluation indicators as an initial set others can build from and extend; third, it describes the first empirical explorations of the multi-lifespan information system design research approach.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.080
GPT teacher head0.243
Teacher spread0.164 · 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