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Record W148464524

One Employee and Several Applications: An Information Management Case Study.

2009· article· en· W148464524 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSoftware Engineering Research and Practice · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicAccess Control and Trust
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingComputer scienceWorkflowAuthorizationRole-based access controlOnboardingAccess controlHuman resource managementAuthentication (law)Computer securityKnowledge managementManagementDatabase
DOInot available

Abstract

fetched live from OpenAlex

In recent years, the use of Role-based Access Control (RBAC) has evolved within organizations such as the Government of Canada (GoC). However, it is not clear that existing on-boarding and off-boarding workflows have been influenced by the emergence of this technology. In this work, an Information Management (IM) case study is executed for one employee in the GoC. Results are summarized by human resource and staffing position and the advantages of onboarding and off-boarding by staffing position are discussed. As the number of applications by employee increase, so too does the cost of the administrative processes. RBAC reduces the cost of administration at the authorization layer and its concepts can be applied at the authentication layer.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.055
GPT teacher head0.401
Teacher spread0.347 · 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