MétaCan
Menu
Back to cohort
Record W1555935098

Recordkeeping Professional Ethics and their Application

2008· article· en· W1555935098 on OpenAlexvenueno aff
Mary Neazor

Bibliographic record

VenueArchivaria · 2008
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsnot available
Fundersnot available
KeywordsLienEthical codeConfusionContext (archaeology)Political scienceSociologyFrenchLibrary scienceHumanitiesLawPhilosophyHistoryPsychologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Cet article examine le concept du code d'thique pour les archivistes et les gestionnaires de documents comme un travail en cours.Il fournit d'abord un court aperu d'un domaine qui connat prsentement des dveloppements thoriques et pratiques importants : le lien entre la gestion thique des documents et les droits humains, surtout l'chelle internationale.Il donne ensuite une analyse plus dtaille des codes d'thique des archives de plusieurs pays anglophones et francophones, ainsi que du Conseil international des archives (ICA) et de ARMA International.L'auteure suggre que les carts entre ces codes nationaux peuvent s'expliquer, au moins en partie, par l'absence de lien avec un contexte socital plus vaste.Elle suggre aussi que cette lacune -et la confusion pour certains de savoir quel public exact est visles affaiblit : si les codes d'thique ne semblent s'appliquer qu' un petit groupe de professionnels et une gamme de questions assez restreinte, ils risquent de devenir dtachs des questions plus larges, et donc de cesser d'tre pertinents l'ensemble de la socit.La prochaine section de l'article comprend trois tudes de cas portant sur la gestion des documents et des situations thiques relles, puis elle examine si l'applica tion des codes d'thique des archives actuels aurait pu influer sur les rsultats obtenus.L'article termine en imaginant quelques dveloppements futurs pour les codes d'thique des archives.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.176

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.104
GPT teacher head0.337
Teacher spread0.234 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueArchivariaSame topicPatient Dignity and PrivacyFrench-language works237,207