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Record W6967186053 · doi:10.5064/f6buax58/hffjnt

Burke_EDI_NENA.NY002.ResearcherSurvey.2017.09.23.pdf

2023· dataset· en· W6967186053 on OpenAlexaff

Bibliographic record

VenueSyracuse University Qualitative Data Repository · 2023
Typedataset
Languageen
FieldEnvironmental Science
TopicEnvironmental Science and Water Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsIdentifierSurvey data collectionPlan (archaeology)Survey methodologyIdentification (biology)Scale (ratio)Data collection

Abstract

fetched live from OpenAlex

Researcher-completed surveys and responses: This survey is used by the researcher to organize and collect data on each organization or program selected as an Energy Democracy Initiatives (EDI). The survey allows the researcher to identify and organize features or attributes for each selected EDI. This survey is not intended for use with non-researcher respondents. At this stage, the researcher completes the survey using publicly available sources as described in the Methods and Data Management Plan (EDI_NENA.MethodsDMP). Future use as a survey instrument would require approval of appropriate research ethics board. To use this survey, the researcher finds sources to identify a response to each question drawing from publicly available sources such as the EDI website. For each question, the researcher enters or selects the response, provides evidence of this response, and provides information on the source of the evidence. If no evidence is available, researcher responds as “unspecified.” Once compiled, the responses are entered into the database of Energy Democracy Initiatives for this research project (EDI_NENA.initiatives). Survey questions: EDI identifier (researcher-assigned); Name of organization or program; Location of organization or program (postal address of main office); Year of initiation; Organization type GS5 (public, private, nongovernmental/nonprofit, community-based, cooperative, hybrid); Initiation/management or leadership A5 (top-down, bottom-up or hybrid); Social performance measures O1 (e.g., efficiency, equity, accountability, sustainability); Ecological performance measures O2 (e.g., overharvested, resilience, biodiversity, sustainability); Social-ecological emphasis or norms A6 (social, ecological, social-ecological); Breadth of focus or mental models A7 (holistic or specific issues); Geographic range or spatial scale GS2 (local, regional, national, global, cross-scalar); Available technologies TS4 (e.g., solar, wind, hydroelectric, all renewables). One survey per selected EDI. Text and numeric data. Revisable (new data may be added and old data may be changed or deleted). Completed researcher surveys are created as text documents using Microsoft Word 2016 (.doc) and converted to Rich Text Format (.rtf) as well as PDF (.pdf) file format using PDF version 1.7 (Acrobat 8.x). EDI_NENA.[two-letter identifier for province/state][three-digit numeric identifier for each unique EDI].ResearcherSurvey.yyyy.mm.dd

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)0.011
metaresearch head score (Gemma)0.037
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: Dataset · Consensus signal: none
Teacher disagreement score0.278
Threshold uncertainty score0.396

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.7220.522

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 head0.099
GPT teacher head0.340
Teacher spread0.241 · 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
GenreDataset

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
Published2023
Admission routes1
Has abstractyes

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