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Trends in Technoethics

2010· book-chapter· en· W4255346663 on OpenAlexaff
Rocci Luppicini

Bibliographic record

VenueAdvances in information security, privacy, and ethics book series · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCyberloafing and Workplace Behavior
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsWorkflowFlexibility (engineering)The InternetComputer scienceEmerging technologiesWork (physics)Information technologyTelecommunicationsKnowledge managementWorld Wide WebEngineeringDatabase

Abstract

fetched live from OpenAlex

The widespread integration of electronic technologies in contemporary organizations is transforming organizational operations and how people work. This can partly be attributed to the advent of reliable technological infrastructures, increased workflow efficiency, and operational cost savings that can be achieved by utilizing electronic technologies. New electronic technologies allow organizational members to exchange more information in less time and with greater flexibility than possible through traditional means. Electronic technology common to organizations includes, but is not limited to, computer monitoring and filtering systems, surveillance cameras, IM and other chat tools, electronic mail and voicemail, Internet, audio and video conferencing tools, personal data assistants, and mobile devices. Non-work-related use of electronic technologies may include personal use of electronic technologies as well as institutional uses of counter measure electronic technologies to control personal use.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0020.006
Scholarly communication0.0090.007
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0300.005

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 head0.025
GPT teacher head0.340
Teacher spread0.315 · 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 designQualitative
Domainnot available
GenreReview

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
Published2010
Admission routes1
Has abstractyes

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