Open-Source Geography » Research and Writing

A Review of (potentially) Geographic Titles from the Journal of Rural Health

Kevin — Thu, 17 Sep 2009 06:18:01 +0000

In keeping with my interests to specialize in the geographical implications of health and access to care, I have decided to focus on the rural aspects of these issues. As such, the academic journal I have chosen to review is the Journal of Rural Health. In the title of the journal introduces the concept of “rural”. In Geography as a discipline, this is a subset of our fundamental notions of “place” or “region.” Many articles are essays on the meaning of the “Rural” concept. That medical and public health researchers write them does not discount that they are doing the work of a Geographer.

The journal is balanced in terms of commentary/qualitative and quantitative methodologies, including GIS technologies. Most articles are about rural U.S. or Canadian health, but there are som international articles. Diseases representative in this journal include HIV/AIDS, diabetes, substance abuse, obesity, cancer, dementia and many others. Positive issues such as well-being or healthy pregnancy are a minority, but still represented. In addition, specific populations are considered, including the elderly, children, both minority and majority populations, economically disadvantaged, physically and mentally impaired, migrant-workers and others.

The research frames specific diseases and/or population segments into any of the following broad themes found in this journal:

Patient Behavior
- Insurance
- Access to Healthcare
  - Geographic
  - Financial
Supply of Medical Facilities and Physicians
Rural and Urban Health Care Comparisons
Physician Behavior
- Migration Patterns
- Physician Training
- Distribution
Policy Analysis
- Legislation Proposals
- Program management
- Effectiveness
Status and Evolution of Rural Hospitals
Attitudes towards treatment or specific diseases
Data and Methods
Technology and Best Practices
Essays about the meaning of RURAL

NOTE: For the review of this journal, I used the search terms “GIS”, “Spatial”, “Geography”, or “Geographic” to identify articles in this journal that have some identifiable geographic component. However, even with these search terms, many of the articles were not inherently geographical. I retained all articles that I found, and then reviewed the titles of 139 articles to detect the types of articles this journal tends to publish. Based on titles alone, I identified 21 articles where researchers behaved as if they were Geographers in their research. Many more have identifiable geographic components, but overall, Geographers have a role in this journal.

Review: A Monte Carlo Approach to Diffusion – Torsten Hagerstrand

Kevin — Mon, 31 Aug 2009 00:12:54 +0000

This article demonstrates how innovations are diffused via “face-to-face” social networks. Its primary method is a probabilistic Monte Carlo algorithm to simulate, and approximate, an observed pattern of innovation adoption. In this case, Hagerstrand studies two farm subsidy programs in Sweden and traces the pattern of their adoption over space and time.

As a side note, Hagerstrand’s body of work after this paper deal with both the temporal aspects of analysis and an attempt to discern social pattern by examining the activities of a group of individuals rather than an aggregation of the group’s social patterns. (“What about People in Regional Science?” 1970). Both themes are present in “A Monte Carlo Approach to Diffusion”.

Considering the 1965 publication, and its quantitative nature, a few research themes emerge. First, the paper is published in The European Journal of Sociology, not Geography. This would suggest that established Geographers had not fully entered into the mindset that Geography could be used to analyze a variety of subject matter in the social sciences. Beyond a generalized entry into the social sciences, Hagerstrand aligns himself with that contemporary embrace of quantitative methods and scientific rigor in Geography during the late 1950’s and early 1960’s. Additionally, he follows the trend of time for social scientists to borrow concepts found in the canon of chemistry and physics. His nod to chemistry is quite overt by using “diffusion” in his title. His discussion of physics is more subtle. For example, in describing the frequency of telephone calls with respect to distance he states on page 371 that “… the relative frequency of calls decreases on average very nearly with the square of the distance.” This is the distance decay parameter found in the definition of Newton’s formulation of gravity.

The access of computational methods in the 1960s, coupled with a need for scientific rigor and quantification positions Hagerstrand as an early leader in the foundations of Geographic Information Sciences. The particular innovation was a Monte Carlo methodology, developed in the body of statistics literature, to study of geographic patterns with social implications. His reliance on probabilistic methods and the use the use of computation methods to analyze geographic distributions reverberates to this day. For example, in the 1990s, Monte Carlo methodologies were used to stabilize outcomes found in aggregations the Modifiable Areal Unit Problem.

Hagerstrand faced many problems while testing the results of his models. The computational requirements to develop simulations that are more advanced were not available at the time. Additionally, he notes at the time of publication, no one had carried out a simulation allowing for direct comparison of an observed pattern. He describes this problem in both simulations. In his first test, even with his assumptions of a uniform population distribution, no barriers to communication, and single adopter in the first generation, a pattern emerges that is visually similar to that of the observed pattern. However, the results are too generalized for direct comparison. He says the same thing about the second simulation, which did factor the uneven population distribution, barriers to communication and the observed three adopters of the bovine tuberculosis subsidy into the simulation.

Hagerstrand believes the spatial data required for this analysis is the location of the adopters and the universe of eligible adopters. In addition, a gridded framework of areal units is required so that both the observed and simulated data can be, in modern terminology, georeferenced. Additionally, probabilities based on observed population and barriers to communication are necessary in approximating the empirical pattern. The location of telephone calls and their receivers and a “to-from” matrix of intra-region migratory patterns, are necessary data for understanding the social network of “face-to-face” communication of innovations.

In this paper, two distinct pieces emerge that reinforce each other. The first is the analysis of a social hypothesis that the “diffusion of techniques and ideas (…occur…) through the network of social contacts.” The second is a well-developed methodology for analyzing the hypothesis. The discipline of Geography had not seen this methodology and this paper helped solidify the use in of computational techniques in general and Monte Carlo techniques in particular.

Outline below the fold

Introduction

“The nebula-like cluster is a common trait in the spatial picture of man’s attributes.”
No simple explanation…
One process is important: diffusion of techniques and ideas through the network of social contacts

The Neighborhood Effect
Diffusion – movement of innovation over space and time
Author sought to analyze spatial aspects of diffusion of innovations. Ideal case:

first introduction of innovation
individual adopters and non-adopters can be discerned

Example innovation: Two different farm techniques followed over 5 years

Subsidy for improvd pasture-land on small farms (to encourage farmers to not use forests for grazing).
- Of all eligible farms, First two years, 3 adopters… 7 more adopters in year 3… 9 in year 4… 5 in year 5
Systematic control of bovine tuberculosis
- All farms eligible
- Spatial order, over time

Reactions of farmers for both innovations

Adopters in more isolated areas step-by-step northward as time progresses

Literature has shown:

“Nearness” plays a role – this pattern of a cluster of adopters, subsequent adopters are located closest to the original clusters from the next set (3rd year) of adopters
patterns detectable at all scales (a hierarchy of scales)

The Network of Social Communication
Author will attempts to demonstrate this pattern of innovation adoption with theoretical experiments

“… evident that nobody can adopt an innovation without first having gained knowledge of its existence”
“adoption not immediate”
Why aren’t the subsequent adopters hearing about the subsidy from the government (or mass media) rather than their neighbors? The original adopters are able to show the subsequent adopters that the program works. To address this issue, the author assumes one means of communicating innovation.
Scalar effects
- Three groups operating at local, regional and international scales
- some operate locally, some operate locally and regionally, some operate at all 3 scales
- “Those belonging to the wider range and having links in common with the lower ones form the channels through which information disseminates between levels

Telephone Traffic

Telephone traffic as a proxy for face-to-face communication
Longer distance phone calls can be inferred to have originated for “supplies” from central places
Shorter distance phone calls are social/fraternal contacts
Phone calls decrease with distance… the relative frequency of calls decrease very nearly with the square of the distance (Distance Decay function/Gravity models)

Gravity models and trip distribution theory (M Schneider – Papers in Regional Science, 1959)

Local Migration
Assumption: constant rates of local migration (Marriage, labor exchange, farm sales) and within existing framework of social connections

The Diffusion Model I
Monte Carlo: A computational method where an existing pattern is approximated and a series of of sample sets are randomly and iteratively generated to simulate that pattern. A model is then generated that uses each iteration of samples to comparing an empirical pattern to the simulated sets.

Revolution: Adoption of physics model, Quantitative Revolution, access to computational methods, use of algorthmic methods to model an empirical pattern, foundation of GIScience, discerning social patterns through individualized activities rather from an aggregate point of view

Assumptions:
1. Isotrpoic Plane
2. Uniform population distribution
Rules

1. One adopter
2. Innovation is adopted when heard of
3. “Information is spread by telling at pair-wise meetings”
4. The telling takes place at constant intervals
5. Distance decay between teller and receiver

Input Data I
Local Migration

Spatial Consequences
1. geometric progression
2. individuals in central cells become less important in contributing to further growth
3. Distribution of adopters becomes irregular

Direct comparison with empirical pattern in generalities only as simulation is idealized, but provides us with a way to study to variations of outcomes on an isotropic surface.
Suggestion to model on a plane that has some irregularities: unevenly distributed population and barriers to communication

Input Data II

Telephone samples
Sample grid framework expanded so that “bouncing” of adoption could be modeled
Each cell assigned a probablity so that cells with many inhabitants have a greater likelihood of being adopted and into account for barriers to communication
Adopters near barriers were less influential as they have fewer contacts
Instead of one adopter from first simulation, 22 potential adopters were chosen and approximated the empirical pattern of eligible farms

Comparisons Between Simulation and Empirical Data

Raw numbers not useful, so isolines are based on percentage of adopters (even though base is raw population base is small)
In Figure 7 (graphs), we see that percentages of adopters to potential adopters shows a negative relationship. as the percentage of potential adopters increases, the percentage of adopters decrease.

Conclusion: The simulation approximates the empirical observations

Questions that you should be ready to answer after reading Torsten Hagerstrand’s “Monte Carlo Approach to Diffusion”.

If you were asked to write one sentence describing the subject matter of this paper, what would you write?
In which of the major research traditions in geography would you place this paper?
Does this paper differ in important ways from most other papers in this research tradition published around this time?
Could this article have been written in 1955 rather than in 1965?
What geospatial data, abstractly defined, does Hagerstrand say is essential for a researcher to have to conduct research in the area he describes?
Does Hagerstrand have anything to say about predicting future spatial distributions?
What are the different roles that empirical evidence plays in this paper?
What are the issues Hagerstrand faced in testing the results of his model?
What other disciplinary sources can you recognize as contributing significant ideas to this paper—other than geography?
Are there other questions you think are important in evaluating this paper?

Article Review: American Metropolitan Evolution

Kevin — Wed, 26 Aug 2009 02:05:34 +0000

American Metropolitan Evolution, by John R. Bochert, offers us a view of how America’s configuration of metropolitan areas has emerged in tandem with epochs of transportation and energy innovations. It draws on historical technological developments to describe the forces by which these urban areas established themselves and subsequently developed. Though populations and hierarchical status may change, the present configuration of major urban centers in America was set at the beginning of the ???? epoch.

Rather than focusing on the urban growth of a single metropolitan area, the author develops the idea that America’s population centers represent a single system with the American (conterminous United States) landmass as a substrate. It also sets itself apart from other works in urban geography by suggesting that previous examinations of systems of cities have lacked a historical context.

It describes four eras of technological innovations and uses them to contextualize the hierarchies. It discusses four major transportation/energy innovations in American history and how together, those led to the pattern of American urbanization as of 1967. The four technological innovations and associated eras are:

The Sail-Wagon Era (1790 to 1830)
The Steamboat and Iron Horse Era (1830 to 1870)
Steel Rail and Electric Power Era (1870 to 1930)
Auto-Air-Amenity (1930 - ) Note: characterized by the internal combustion engine and a shift to a service based economy

The maps show a westward moving frontier that transforms a sparsely populated landmass by depositing human settlements along the way.

In addition to the westward movement of population, in each era technologies developed that reinforced a shift from agricultural to urban population growth. For example, the internal combustion engine meant, with tractors, the food production system would require fewer number farmers to produce the food requirement for an urban area. In turn, the labor needs shifted from rural areas to urban.

Once the historical context is established, the author categorizes metropolitan areas by size and develops rankings and comparisons within each of the four technological epochs described above. In doing so, the author provides a framework to observe the westward expansion of the American population and its settlement patterns.

OBSERVATIONS

The scope of this article encompasses the entirety of American history, its westward expansion and pattern of population settlement. It does leave out many details, but does so by working at a national scale where such omissions/generalizations are required. However, these generalizations provide us with a cartographic narrative for how the American landscape transformed into urbanized space in tandem with major eras of technological innovation.

The author provides the reader with a blend of historical context and sound methodology. The first third of the paper describes in detail the technological eras and their impact on urbanization. The next third is a description of method for how metropolitan areas ranked within each technological epoch. The final third is observation and discussion.

What is notable is this paper’s readability. With a few exceptions, technical jargon is at a minimum and concepts beyond the grasp of the average reader are few.

Research and Writing in Geography – Session 1

Kevin — Tue, 25 Aug 2009 03:18:22 +0000

The Research and Writing in Geography course is a seminar where a reading is discussed each session. Two students are assigned the task of providing written commentary and leading a discussion of the reading. It is a team-lead course (Rex Honey, Gerard Rushton and George Malanson) who provide the readings and prepare discussions of the state of professional research in Geography. During the course, one of the three pre-dissertation writings will be complete.

As the students prepare to discuss the weekly readings, consider the following questions:

What was the author trying to do?
Did the author accomplish their goal?
Why is this an exemplary work in the discipline of Geography?
How did it change the course of research in Geography?

The upcoming reading for August 30, 2009 is Borchert’s “American Metropolitan Evolution.”

Gerry Rushton discusses how people behave in space. What sort of rules govern the spatial behavior? And how do those rules manifest themselves into a spatial organization? Though he started his career in theories of location of firms and other economic entities, but has moved to research into optimal location, based on allocation of resources, of services; particularly schools and health facilities. Furthermore, an optimally located facility can have a measurable output in pre-determined healthfulness or educational goals. I found it particularly interesting his discussion that “methods of optimal location” are not often found in a likely place. That is, quantitative geography textbooks. The reason being that these texts are often written by statisticians when these methods are often algorithmic and/or found in operations research rather than pure statistical analysis.

Rex Honey provided some interesting discussion about political geography and justice. How do political entities concieve of a “just society?” How do these entities create laws/constitutions and what are those spatial impacts? How does the way we partition space affect the delivery of municipal services? I am wondering about the multiscalar (jurisdictional) effects of these issues. Also, he has a paper being reprinted called “Form, Process and the Political Organization of Space,” that I am looking forward to reading.

George Malanson is a biogeographer studying patterns of floral distributions in the Rocky Mountains.