The Practice of Mapmaking: Bridging the Gap between Critical/Textual and Ethnographical Research Methods
Bibliographic record
Abstract
The recent shift from representation to practice within map theorization has led to a renewed interest in mapmaking calling for both closer attention to the practices involved and the employment of ethnographic methodologies in researching how maps come to life. A deep understanding of the making of maps, however, requires a combination of different approaches, from the critical (text-oriented) to the ontogenetic (practice-oriented), from deconstruction to narrative ethnography, and from cultural contextual readings to subjects-centred readings. Two map scholars with very different backgrounds (phenomenology and political geography) seek to put these different approaches into action while investigating mapmaking through a single case study. The life and work of Laura Canali, who has created maps for Limes: Rivista Italiana di Geopolitica (the leading publication in Italy in the field of international relations) since 1993, are analyzed to show how ethnography and critical reading are better used as complementary rather than conflicting approaches. Comparison of the methodological framework applied here with more traditional approaches employed in the field of historical cartography provides evidence of present-day changes in mapmaking and calls for an enhancement of new practice-oriented methods of analysis. Finally, additional insights from creativity studies suggest that there is an interesting line of research on “cartographic creativity” to be further developed.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.180 | 0.163 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.010 | 0.099 |
| Scholarly communication | 0.034 | 0.041 |
| Open science | 0.006 | 0.018 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".