Analyser la disponibilité de l'Information géographique numérique dans les enjeux de suivi et de gestion du trait de côte : application aux cas breton (France) et québécois (Canada)
Bibliographic record
Abstract
In the context of monitoring and coastline management issues, the need for information and knowledge accessible on the web is described as a major issue by the French and Quebec public authorities. Nevertheless, on this subject, the strategy of the developers of Spatial Data Infrastuctures (SDI) and open data platforms as well as the mechanisms of access to the contents of these devices are still relatively unknown to managers and citizens. We question the characteristics of the informational regime by the systematic analysis of its organizational, thematic, temporal characteristics of data and entering the context of the instrumentation of public action. To do this, the extraction of a geoinformational patrimony (metadata) was carried out using lexical terms characteristic of the discourse on coastline monitoring and management issues in France and Quebec. The goal of this thesis work is to propose a methodology approach questioning the issues of avaibility of digital geographic information in two stages and tested in territorial and coastal contexts with differentiated socio-political characteristics.On the one hand, the thesis explores the structural aspects of access to digital geographic information by questioning the structure of such devices on the web.On the other hand, it examines the availability of content on devices endowed with a cataloguing service. Statistical and graphical analysis of hypertextual components and web services as well as the analysis of geographic data reveal asymmetry effects in the availability of geographic information as well as data standardization phenomena on the coastal environment. However, we observe a heterogeneous range of geographic data services.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".