Highways, law and governance : Parish of Halifax, c.1550-1700
Bibliographic record
Abstract
Transport historians have made an increasingly strong case for connectivity and mobility in Stuart England even before the introduction of turnpike trusts in the eighteenth century. There has, however, been little explanation of how this was achieved at local level, nor has the broader historiography of government in this period given infrastructure the attention it merits, since the painstaking, but dated, research, of the Webbs. This study explores the diversity of approaches to the administration of highway infrastructure by the townships of Halifax parish in addressing a range of travel and transport needs on foot and horseback in an upland area largely inaccessible to wheeled vehicles. The research is concerned with how townships managed their highways, who the officeholders were, how they negotiated relationships with other agents and institutions, and the implications of a reconceptualisation of the highways function for current debates on state formation. Exploiting excellent manorial and township records, the analysis takes advantage of GIS mapping techniques to re-evaluate the governance of highways, as townships in the parish responded to statutory, political and socio-economic change. A review of the legal framework shows how the Tudor co-option of manorial courts for monitoring statutory compliance resulted in a hybrid system of tenurial liability and communal obligation. Broad-based participation was subject to increasing middling-sort assertiveness, and records from Sowerby township testify to precocious funding of maintenance from the constables’ rates, supervised by a powerful vestry. Economic activities, such as pastoral agriculture, textile manufacturing, mining and quarrying, and the service sector were significant drivers of road management priorities. The research argues that manorial and township institutions deserve more recognition for creative and effective solutions to problems of access and connectivity through presentment routines. Success in managing highways in the parish depended on the participation of better-off landholders both as officeholders and in discharging individual and collective obligations for maintenance and cleansing. The institutions of manor and vestry provided legitimacy to the governance of the highways function, and thereby contributed to the resilience of the seventeenth-century state.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".