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Record W3211582933 · doi:10.54590/pop.2021.004

Social Analytics Through Spyral

2021· article· en· W3211582933 on OpenAlex
Geoffrey Rockwell, Kaylin Land, Andrew MacDonald

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePop! Public Open Participatory · 2021
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsnot available
Fundersnot available
KeywordsJavaScriptComputer scienceAnalyticsWorld Wide WebDevelopment environmentCode (set theory)Data scienceSoftware engineeringProgramming languageHuman–computer interaction

Abstract

fetched live from OpenAlex

In this paper we introduce Spyral, a notebook environment that works in tandem with Voyant Tools. Voyant Tools is an online digital text analysis environment. Spyral notebooks extend Voyant and allow users to create JavaScript online notebooks with both text and code cells. These notebooks are designed to allow for collaboration between scholars. We also discuss both the possibilities and some limitations of the notebook environment. We provide examples of both tutorial notebooks that can be used for pedagogical purposes as well as examples of Spyral notebooks used in collaborative analysis. Finally, we suggest potential areas for further development for Spyral.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.002
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 head0.273
GPT teacher head0.419
Teacher spread0.145 · 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