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Record W2492161979 · doi:10.1002/9780470592663.indsub2

Subject Index: Volume 3

2009· other· en· W2492161979 on OpenAlexaboutno aff
Kenneth H. Silber, Wellesley R. Foshay, Ryan Watkins, Doug Leigh, James L. Moseley, Joan C. Dessinger

Bibliographic record

Venuenot available
Typeother
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)Index (typography)Volume (thermodynamics)MathematicsComputer scienceLibrary scienceThermodynamicsWorld Wide WebPhysics

Abstract

fetched live from OpenAlex

Boxes Model on, 18fig-19 Behavior engineering model (BEM): cause analysis used in, 248; description of, 99 Blogs, 309, 310 Boston Public Schools, 340 Brinkerhoff's impact map, 344 Brinkerhoff's stage model, 343 Brinkerhoff's success case method, 344 Broadcaster.com, 301 Budget assessment, 235-236 Business needs: assessing strategic or operational, 99; BSC (balanced scorecard) perspective on, 319; ROI process model alignment with, 234; ROI process model identification of, 225. See also Organizations C Calendar time, 20-21fig Calibration: definition of, 12; performance applications of, 12-14 Canadian Evaluation Society, 38 Casey Foundation, 286, 288 Causation: correlation compared to, 193-194; definition of, 194 Cause analysis: behavior engineering model (BEM), 248; HPT evaluation model step of, 248t-249 Centers for Disease Control and Prevention (CDC): evaluation work plan using framework of, 284-285t, 286; public health evaluation approach used by, 284, 294 Certification: for full-time evaluators, 365; for part-time evaluators, 365-368; project management, 365-366. See also Profession Certification Guide (Weinberg), 355 Certified Performance Technologist (CPT), 367-368 Certified Professional in Learning and Performance (CPLP) credential, 368 Change: beware of lurking monsters within, 270-271; critical success factors for, 266; interrelationships between clients and, 268-270; selection of specific, 264-266; value, sequence, and timing of, 266-268. See also HPT projects; Performance interventions Change process: HPT evaluation model implementation for, 251-253; impact evaluation process and, 124-125; organizational enablers of, 257-258 Checklists: performance, 216fig; selfinstructional training, 149e-150e Chi-square goodness of fit, 193 Classes of information data, 291-292t, 293 Clients: ethical dilemma of data collection interference by, 169; HTP professionals' ethical relationship with, 167; interrelationships between changed interventions and, 268-270 Code of Ethics (ASQ), 367 Code of Ethics (ISPI), 161, 166, 171. See also Ethical issues The Cognitive Style of PowerPoint (Tufte), 172 Communication tools: performance conversations as, 55-56; podcasts and webcasts, 299-300; social network websites, 300-301; web-based surveys, 300. See also Reporting Competency-based needs assessments,

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.094
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0020.001
Scholarly communication0.0080.005
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.9060.876

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 head0.146
GPT teacher head0.486
Teacher spread0.340 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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".

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Citations1
Published2009
Admission routes1
Has abstractyes

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