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Record W7065560180

ERIC ED477400: Employer of Choice? Workplace Innovation in Government: A Synthesis Report.

2001· other· en· W7065560180 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2001
Typeother
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringHuman resourcesWorkforceLaggingGovernment (linguistics)Private sectorWork (physics)Public sector
DOInot available

Abstract

fetched live from OpenAlex

The Human Resources in Government project examined the impact of extensive downsizing and restructuring in Canada's public service sector and sought innovative ways of making Canada's governments "employers of choice." The project focused on Canada's federal government and the governments of Alberta, Manitoba, Ontario, and Nova Scotia. The project's main finding was that Canada's government agencies must become more flexible, knowledge-intensive, and learning-based workplaces. The project established that, as of the late 1990s, the five governments studied had not moved very far on creating the conditions enabling more innovative approaches to work organization and human resource management. Although training and information technology were generally in place, some of the governments and work units studied were lagging behind. Although innovative workplace practices were progressing at a fairly impressive pace when compared to the private sector, there remained a large untapped potential for organizational reform to improve the quality of working life and contribute to workforce renewal. The importance of building knowledge-based organizations, implementing creative recruitment and retention strategies, creating rewarding work environments, and resolving compensation dilemmas was emphasized. (A discussion of the design and methodology of the Human Resources in Government Project is appended. Fifty-seven endnotes and the names/addresses of the project's advisory committee members are included.) (MN)

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.114
Threshold uncertainty score1.000

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)0.1150.001

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2001
Admission routes1
Has abstractyes

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