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Technoethics

2010· book-chapter· en· W4256113685 on OpenAlexaff
Rocci Luppicini

Bibliographic record

VenueAdvances in information security, privacy, and ethics book series · 2010
Typebook-chapter
Languageen
FieldDecision Sciences
TopicTechnology's Impact on Media
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSalientEngineering ethicsGovernment (linguistics)Political scienceEthical issuesPublic relationsHealth careBusinessEngineeringLaw

Abstract

fetched live from OpenAlex

A major struggle within our evolving knowledge society is that increasingly potent scientific and technological growth is forcing individuals to re-examine how technology is viewed. This is especially salient in the pure and applied sciences where technological developments offer ways to surpass current human capacities and affect life in ways that were not imaginable fifty years ago. New breakthroughs in medicine, information and communication technology, transportation and industry are juxtaposed with growing needs to deal with moral and ethical dilemmas associated with new technological developments. Increased reliance on new technology creates fundamental challenges revolving around security and privacy issues, access issues to education and health care, legal issues in online fraud and theft, employer and government surveillance, policies issues in creating and implementing ethical guidelines and professional codes of conduct, along with ethical dilemmas in a number of vital areas of research and development.

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)0.005
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.010
Scholarly communication0.0080.006
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0510.012

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 head0.056
GPT teacher head0.378
Teacher spread0.322 · 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 designTheoretical or conceptual
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

Citations0
Published2010
Admission routes1
Has abstractyes

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