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Educational and Professional Technoethics

2010· book-chapter· en· W2476748197 on OpenAlexaff
Rocci Luppicini

Bibliographic record

VenueAdvances in information security, privacy, and ethics book series · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHappeningUploadThe InternetSociologyPublic relationsPolitical scienceEngineering ethicsMedia studiesInternet privacyEnvironmental ethicsEngineeringWorld Wide WebComputer scienceArtPhilosophy

Abstract

fetched live from OpenAlex

Are we developing a (global) society where our youth think it is ok to copy and paste whatever they see on the Internet and turn it in for homework; where writing an English paper would include BTW, IMHO, LOL among other emoticons; where downloading a song or movie that they can pirate from the Web is perfectly ok? We would certainly hope not. However, these concerns are just the tip of what is happening in our society. When looking at the social impact of technology in on our society it becomes clear the importance of instilling ethical behaviors and practices in the members of our society. Where is the best place to instill these ethical behaviors? --Gearhart, 2008, p.263.

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 categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0410.010

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 head0.021
GPT teacher head0.337
Teacher spread0.317 · 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
GenreMethods

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

Citations1
Published2010
Admission routes1
Has abstractyes

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