‘The whole is always smaller than its parts’ – a digital test of Gabriel Tardes' monads

In this paper we argue that the new availability of digital data sets allows one to revisit Gabriel Tarde's (1843–1904) social theory that entirely dispensed with using notions such as individual or society. Our argument is that when it was impossible, cumbersome or simply slow to assemble and to navigate through the masses of information on particular items, it made sense to treat data about social connections by defining two levels: one for the element, the other for the aggregates. But once we have the experience of following individuals through their connections (which is often the case with profiles) it might be more rewarding to begin navigating datasets without making the distinction between the level of individual component and that of aggregated structure. It becomes possible to give some credibility to Tarde's strange notion of ‘monads’. We claim that it is just this sort of navigational practice that is now made possible by digitally available databases and that such a practice could modify social theory if we could visualize this new type of exploration in a coherent way.     

On Recalling ANT

This paper explores one after the other the four difficulties of actor-network theory, that is the words 'actor', 'network' and 'theory'—without forgetting the hyphen. It tries to refocus the originality of what is more a method to deploy the actor's own world building activities than an alternative social theory. Finally, it sketches some of its remaining potential.     

Risk Target: An Interactive Context Factor in Risk Perception

The effect of specification of the target on risk evaluation was examined. A whole set of hazards, covering most of the domains, were considered: common individual hazards, outdoor activities, medical care, public transportation, energy production, pollutants, sex, deviance, and addictions. Three human targets were introduced: personal health risk (including personal risk of death), health risk for people in the country, and health risk for people in the world. The basic design was a between-subjects design. The first hypothesis was that risk judgments made in the "world" condition should be higher than risk judgments made in the "country" condition, and risk judgments made in this condition should be higher than risk judgments made in the "personal" condition. This is what was observed. The second hypothesis was that the target effect should differ as a function of the kind of hazards considered. This also is what was observed. In two domains--pollutants, and deviance, sex, and addictions--the target effect was important. It corresponded to about one-tenth of the response scale. In the four remaining domains, the target effect was unimportant or absent.     

Motivation as a limit to pricing

A monetary reward offered by a principal tends to crowd out an agent's willingness to perform the task for its own sake (i.e. based on intrinsic motivation) if the agent's sense of recognition, fairness, or self-determination are thereby negatively affected. The crowding-out effect of pricing may also spill over into sectors where no pricing is applied (spillover effect) if the persons affected find it costly to dinstinguish their motivations according to sectors. Motivation crowding-out and spillover narrow the scope for successfully applying monetary rewards. These theoretical claims are supported by real-life observations for environmental policy and blood donations.     

Health and the Quality of Life

The aim of this investigation was to explain theimpact of peoples self-reported health on theirlevels of satisfaction with their health, and theimpact of these things plus satisfaction with otherspecific domains of their lives on the perceivedquality of their lives. The latter was operationalized as general happiness, satisfactionwith life as a whole and overall satisfaction with thequality of life. Seven hundred and twenty-three (723)usable questionnaires returned from a mailout randomsample of 2500 households of Prince George, BritishColumbia in November 1998 formed the working data-setfor our analyses. Among other things, mean respondentscores on the SF-36 health profile were found to belower than published norms from the UK, USA,Netherlands and Sweden, but higher than scores fromAberdeen, Scotland. Mean scores on the CES-Ddepression scale also indicated that our respondentstended to have more depressive symptoms thancomparison groups in Winnipeg and the USA. A review oftrends in mean scores on 17 quality of life items(e.g., satisfaction with family life, financialsecurity, recreation, etc.) from 1994, 1997 and 1998revealed that there were only 7 statisticallysignificant changes across the four year period andthey were all negative. Multivariate regressionanalysis showed that health status measured with avariety of indicators could explain 56% of thevariation in respondents reported satisfaction withtheir health. A combination of health status plusdomain satisfaction indicators could explain 53% ofthe variation in respondents reported happiness, 68%of reported life satisfaction and 63% of reportedsatisfaction with the overall quality of life. Sixtypercent of the explained variation in happiness scoreswas attributable to self-reported health scores, whileonly 18% of the explained variation in satisfactionwith life and with the overall quality of life scoreswas attributable self-reported health scores.     

Healthy Days,Health Satisfaction and Satisfaction with the Overall Quality of Life

In this note we report results of 6 surveysusing the United States Centers for DiseaseControl and Prevention indicators of healthstatus, taken from the Behavioral Risk FactorSurveillance System. Generally speaking, wefound that the CDC healthy days variables couldplay a useful role in survey research aimed atassessing the impact of measured health statuson people's satisfaction with their own healthand with the overall quality of their lives.More precisely, using stepwise regressions wefound: (1) The three healthy days variablesexplained from 16 to 27 percent of the variancein General Health scores. The limited activitydays variable remained as a significantpredictor in only one of the six regressionsand the not good physical health days variablewas most influential in every sample. (2) Thethree healthy days variables explained from 19to 32 percent of the variance in healthsatisfaction scores, and the not good physicalhealth days variable was again most influentialin every sample. (3) The three healthy daysvariables explained from 12 to 39 percent ofthe variance in quality-of-life satisfactionscores, with the not good mental healthvariable most influential in every sample. (4)The four CDC variables together explained from40 to 55 percent of the variance in healthsatisfaction scores, with the General Healthvariable always dominating the set ofpredictors by a fairly wide margin. (5) Thefour CDC variables together explained from 17to 28 percent of the variance inquality-of-life satisfaction scores, with theGeneral Health variable most influential inthree samples and the not good mental healthvariable most influential in the other three.(6) When the four CDC variables plus the healthsatisfaction variable were used as potentialpredictors, we were able to explain from 29 to40 percent of the variance in quality-of-lifesatisfaction scores. In every sample, theGeneral Health and limited activity daysvariables had no significant impact. (7) Usingstructural equation modeling, we found GeneralHealth does not have a direct effect onsatisfaction with the overall quality of lifebut rather only an indirect effect throughhealth satisfaction. The General Health, notgood physical health, and not good mentalhealth days variables account for 51% of thevariation in health satisfaction, and healthsatisfaction, not good physical health and notgood mental health days variables account for30% of the variation in satisfaction with theoverall quality of life.     

Revised GRASP with path-relinking for the linear ordering problem

The linear ordering problem (LOP) is an NP\mathcal{NP}-hard combinatorial optimization problem with a wide range of applications in economics, archaeology, the social sciences, scheduling, and biology. It has, however, drawn little attention compared to other closely related problems such as the quadratic assignment problem and the traveling salesman problem. Due to its computational complexity, it is essential in practice to develop solution approaches to rapidly search for solution of high-quality. In this paper we propose a new algorithm based on a greedy randomized adaptive search procedure (GRASP) to efficiently solve the LOP. The algorithm is integrated with a Path-Relinking (PR) procedure and a new local search scheme. We tested our implementation on the set of 49 real-world instances of input-output tables (LOLIB instances) proposed in Reinelt (Linear ordering library (LOLIB) 2002). In addition, we tested a set of 30 large randomly-generated instances proposed in Mitchell (Computational experience with an interior point cutting plane algorithm, Tech. rep., Mathematical Sciences, Rensellaer Polytechnic Institute, Troy, NY 12180-3590, USA 1997). Most of the LOLIB instances were solved to optimality within 0.87 seconds on average. The average gap for the randomly-generated instances was 0.0173% with an average running time of 21.98 seconds. The results indicate the efficiency and high-quality of the proposed heuristic procedure.     

The Impact of Rainfall on the First Out-Migration: A Multi-level Event-History Analysis in Burkina Faso

Using event history analyses, we investigate the impact of rainfall conditions — a crucial environmental factor in the livelihood of Sahelian households— on the risk of the first village departure in Burkina Faso. The distinction of migrations by destination and duration proves critical in studying this relationship. Findings suggest that people from the drier regions are more likely than those from wetter areas to engage in both temporary and permanent migrations to other rural areas. Also, short-term rainfall deficits tend to increase the risk of long-term migration to rural areas and decrease the risk of short-term moves to distant destinations.