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Record W7095489870

Subordinates ' Assessments of Leadership in the Canadian Army I AB-41-Paper Subordinates ' Assessments of Leadership in the Canadian Army

2016· article· en· W7095489870 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsAction (physics)Service (business)Quality (philosophy)Action researchService qualityFocus group
DOInot available

Abstract

fetched live from OpenAlex

In 1995, in response to direction from the Commander of the Army, a research team conducted a series of focus groups with some 900 service personnel to evaluate "morale in the Army. " In their 1995 final report entitled "Modernization of the quality of life in the Army-Final report, " the team offered a total of 110 recommendations (later refined into 39 critical content areas) considered significant for the improvement of quality of life (QOL) in the Army. Between March and July 1996, Commander LFC issued a series of five action directives in which he stated his intent to change what he could with a view to improving QOL in the Army. At the same time, he directed that subordinate commanders take what actions they could. In 1997, the Personnel Research Team (PRT) was commissioned to assist in the development of indices by which the effectiveness of improvements could be measured. In response to this request, Eyres (1997) recommended that PRT's "Conditions of Service Questionnaire " (COSQ), now known as the Quality of Life (QOL) Survey, become the primary tool with which to gauge the success of measures implemented. A

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.055
Threshold uncertainty score0.398

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0080.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.319
GPT teacher head0.333
Teacher spread0.013 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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