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Record W6917661520 · doi:10.57912/23840349

A study of in-service training as a function of management in federal government

2023· dissertation· en· W6917661520 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

VenueAmerican University Research Archive · 2023
Typedissertation
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Function (biology)Administration (probate law)Training (meteorology)Quarter (Canadian coin)Process (computing)Human resource management

Abstract

fetched live from OpenAlex

The increasing importance that is being placed upon the role of personnel administration and management in the Federal Government affords many research opportunities for the student of Public Administration. Today, there is a challenging opportunity for research in the process of training and development of personnel, and particularly in the field of in-service training. During the past quarter of a century there have been many studies and literature on the subject of training, but because of the dynamic setting in which personnel administration and management function, there is a need for continuous study. Irrespective of the importance that is now being given to personnel management in the Federal Government, there appears to be a lack of emphasis placed upon in-service training and development of personnel as a responsibility of management. It is because of this increasing importance of personnel management, the apparent need for greater emphasis on in-service training as a function of management, and the personal interest of the author in the subject, that this study has been undertaken. The study has involved a survey of outstanding literature in the field of training, governmental and industrial; personal observations of training concepts and practices, governmental and industrial; and personal experience as an in-service training staff member in departments of the Federal Government.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.095
GPT teacher head0.390
Teacher spread0.295 · 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