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Record W4393307194 · doi:10.3992/jgb.19.2.i

COMMUNICATION SKILLS AND REPORT WRITING FOR BUILDING SCIENTISTS

2024· article· en· W4393307194 on OpenAlexaff
Katie C. Russell, Sheldon Jeter, Colin MacDougall

Bibliographic record

VenueJournal of Green Building · 2024
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsQueen's University
Fundersnot available
KeywordsArchitectural engineeringEngineering

Abstract

fetched live from OpenAlex

ABSTRACT Communication Skills and Report Writing for Building Scientists addresses the primary questions of inexperienced technical writers: “How should my report be written?” and “How do I present my work in style, format, data presentation and illustration program?” An undergraduate research report is given as an example of good report writing and key elements of the report are highlighted for student learning. This concise handbook also covers writing to land a job or applying to graduate school, and a step-by-step guide is provided on how to successfully navigate the job search or graduate school application process. Several sample resumes are provided as well as effective means to communicate with prospective employers or graduate programs of interest. The last section of this guide covers writing on the job and speaks to the kinds of tasks students face when they make the transition from classroom reporting to workplace communication, where problems are often open-ended and audiences cannot be assumed to be building science professionals. Instruction is also given to students on how to use the library as a research tool and how to master various virtual communication platforms: Zoom, Microsoft Teams and LinkedIn.

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)0.011
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 score0.760
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
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 integrity0.0000.001
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 head0.038
GPT teacher head0.438
Teacher spread0.400 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2024
Admission routes1
Has abstractyes

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