Information Governance and Assurance: Reducing Risk, Promoting Policy
Notice bibliographique
Résumé
In this chapter, we will examine the external drivers which influence organisations towards practising good information governance.These are pieces of legislation, regulation and standards which are imposed from outside the organization, and which either must be complied with in order to avoid penalties, or which define benchmarks against which the practices and performance of the organization can be judged.Sometimes these, in particular the pieces of legislation, are themselves referred to as 'information governance', in that they impose rules which govern what organizations do with information.However, as we've seen in chapter 1, a more constructive way of understanding the term is to think of 'information governance' as those practices which lead to efficient, effective and ethical use of information, the avoidance of legal repercussions being a sign of legislative recognition of the legal correctness of these practices.The specific laws and regulations dealt with in this chapter will be those which apply in the UK, as space does not permit discussion of equivalent legislation in other legislatures, but it will be found that similar legislation exists in a large number of countries -in March 2013, Rwanda became the 94 th country to pass a Right to Information Act (freedominfo.org2013), the equivalence of EC countries' data protection laws to those in the UK is discussed in section 4.10 below, as is the list of 'third' countries recognized by the EC as having equivalent legislation.Other states, including the twenty-one members of the Asia-Pacific Economic Co-operation Group (APEC) have agreed on privacy principles, and Argentina, Canada, Hong Kong, Israel and Russia have modeled their laws on the European model (Kuner 2010).The United States has had a Freedom of Information Act since 1966.It applies to records held by federal agencies, such as the Department of Justice and the Department of Health and Human Services, and gives individuals the right to access any agency record, except for those protected from public disclosure for reasons of national security, for example.It also requires the agencies to automatically publish other information, including lists of Frequently Asked Questions and answers to them (FAQs).It is the enquirer's responsibility to determine which agency has the records they require, but all agencies have a web site which lists the types of records they hold.This stance of actively making records available is endorsed as good policy by the UK Information Commissioner's Office, and we shall discuss later why it is a part of a well-thought-out information governance policy.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,056 | 0,113 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,006 | 0,024 |
| Communication savante | 0,026 | 0,037 |
| Science ouverte | 0,002 | 0,014 |
| Intégrité de la recherche | 0,010 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».