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Record W4297914324

Du quantitatif au qualitatif : vers une compréhension globale des dynamiques sociales à la forêt. Enquêtes qualitatives réalisées à Tours (région Centre), dans les Ardennes (vallées de la Semoy et de la Meuse) et à Orcines (Puy de Dôme)

2008· preprint· fr· W4297914324 on OpenAlexaff
N. Lewis, Philippe Deuffic

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2008
Typepreprint
Languagefr
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsDynamics (music)Social dynamicsQualitative propertyData scienceGeographySociologyComputer scienceSocial sciencePedagogy
DOInot available

Abstract

fetched live from OpenAlex

/ En décembre, 2004, l'Office national des forêts (ONF), en collaboration avec le Cemagref et le LASMAS de l'Université de Caen a réalisé une enquête quantitative nationale sur les pratiques et perceptions des français vis-à-vis de la forêt. Ce rapport explore par des enquêtes qualitatives locales trois aspects complémentaires à l'enquête de 2004 à savoir : les pratiques et perceptions de l'espace forestier par les femmes à Tours, la question de la fermeture du paysage dans les environs de Clermont-ferrand, la prise en compte du paysage dans les Ardennes primaires.

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)0.024
metaresearch head score (Gemma)0.023
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0020.013
Scholarly communication0.0130.018
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.301
Teacher spread0.276 · 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
Published2008
Admission routes1
Has abstractyes

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