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Record W2398310990 · doi:10.63744/tnnsa4tvw3ab

Video-gaming, Paradise Lost and TCP/IP: an Oral History Conversation between Ray Siemens and Anne Welsh

2012· article· en· W2398310990 on OpenAlexaboutno aff
Ray Siemens, Anne Welsh, Julianne Nyhan, Jessica Salmon

Bibliographic record

VenueDigital humanities quarterly · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsIBMSiemensMedia studiesConversationReading (process)The InternetLibrary scienceSociologyHumanitiesComputer scienceEngineeringWorld Wide WebArtPolitical science

Abstract

fetched live from OpenAlex

This extended interview with Ray Siemens was carried out on June 21st at Digital Humanities 2011, Stanford University. It explores Siemens' early training and involvement in the field that is now known as digital humanities. He recalls that his first experience with computing was as a video gamer and programmer in high school. He had the opportunity to consolidate this early experience in the mid-1980s, when he attended the University of Waterloo as an undergraduate in the department of English where he undertook, inter alia, formal training in computing. He communicates strongly the vibrancy of the field that was already apparent during his graduate years (up to c. 1991) and identifies some of the people in places such as the University of Alberta, University of Toronto, Oxford, and the University of British Columbia who had a formative influence on him. He gives a clear sense of some of the factors that attracted him to computing, for example, the alternatives to close reading that he was able to bring to bear on his literary research from an early stage. So too he reflects on computing developments whose applications were not immediately foreseeable, for example, when in 1986 he edited IBM's TCP/IP manual he could not have foreseen that by 1989 TCP/IP would be firmly established as the communication protocol of the internet. He closes by reflecting on the prescience of the advice that his father, also an academic, gave him regarding the use of computing in his research and on his early encounters with the conference scene.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0180.017
Scholarly communication0.0100.007
Open science0.0010.006
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0120.002

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 head0.062
GPT teacher head0.225
Teacher spread0.163 · 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.

Study designQualitative
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

Citations6
Published2012
Admission routes1
Has abstractyes

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