A Tool for Specifying the Dynamics of School-to-Work Transitions, Social Reproduction, and Social Trajectories: The AGIC Calculator

Guy Tchibozo

LISEC UR 2310, Université de Strasbourg, France

Education Thinking, ISSN 2778-777X – Volume 4, Issue 1 – 2024, pp. 35–38. Date of publication: 5 March 2024.

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Cite: Tchibozo, G. (2024). A tool for specifying the dynamics of school-to-work transitions, social reproduction, and social trajectories: The AGIC Calculator. Education Thinking, 4(1), 3538.


Declaration of interests: The author declares to have no conflicts of interest.

Authors note: Guy Tchibozo is a member of LISEC, the education research centre at Strasbourg University, France. His research focus is on education policy and vocational education and training. (ORCID: https://orcid.org/0000-0001-5865-7900
http://www.lisec-recherche.eu/membre/tchibozo-guy, 01.tchibozo@gmail.com, https://gtsite.xyz/1/)

Copyright notice: The author of this article retains all his rights as protected by copyright laws. However, sharing this article – although not in adapted form and not for commercial purposes  is permitted under the terms of the Creative Commons Attribution-NonCommercial–NoDerivatives BY-NC-ND 4.0 International license, provided that the article’s reference (including the author’s name and Education Thinking) is cited.

Journal’s areas of research addressed by the article: 19-Education Policy; 29-Guidance & Counselling; 40-Measurement & Statistics; 51-Quantitative Research Methods; 56-School-to-Work Transition; 60-Sociology of Education.


One of the best-known criticisms of traditional education systems concerns their deterministic impact on the social trajectory of learners, which maintains and reinforces social inequality. However, previous analysis (Tchibozo, 2004) has shown that the effect of schools on learners’ education-to-work transitions can be not only deterministic, but also random or chaotic. A new tool, the AGIC Calculator, has recently been developed to enable educators, guidance counsellors, policy makers and researchers to specify in a practical way the dynamics of learners’ school-to-work transitions and to analyse more precisely social reproduction, and more generally to precisely analyse the dynamics of any type of social trajectory. This note outlines the main points of the problem and the value of the AGIC calculator for guidance counselling, education policy and research in this field.


Bourdieu; Education-to-work; Guidance counselling; Information, advice, and guidance; School-to-work; Social determinism; Social dynamics; Social reproduction; Social trajectories.

From the 1960s onwards, Bourdieusian critique of school emphasised the role of schools in reproducing social inequalities. Analyses in this vein point to the social determinism exerted by the educational system: it is the children of the elites who get the most out of school and thus have the best chance of attaining elite positions in society.

Most of this message remains true today. However, the situation has become considerably more complex since the 1960s. International and national policies have been pursued to democratise access to high-quality schools. In many countries, upward social mobility has been encouraged. Above all, the school landscape itself has undergone profound diversification, particularly in terms of institutional categories, educational philosophies, training objectives, pedagogical approaches, assessment and certification methods, programmes and curricula, types of learners, learning environments, and school climate. We can no longer limit ourselves to a generic vision of the effect of the school: schools are diverse, and so are their effects.

Therefore, it is important to be able to distinguish between the different effects that schools can have on the social trajectories of learners. In addition to trends in terms of social determinism, upward mobility or downgrading, schools generate a whole dynamic of trajectories. In an initiating article (Tchibozo, 2004), I showed that learners’ career paths can be not only deterministic, but also random or chaotic. Trajectories are purely deterministic when it is certain that two students in identical initial situations will, at the end of identical educational and professional stages, end up at the same point of arrival, for example in terms of professional position or salary. Purely deterministic trajectories are governed by an exact law. Trajectories are random when the same students in identical initial situations have only a chance (i.e., a probability but no absolute certainty) of both reaching the same point of arrival. Uncertainty results from differences that arise between individuals’ situations during the various stages of the pathway. Such differences can persist over time, which defines stable stochastic trajectories. Alternatively, they can instead gradually decrease (convergent stochastic trajectories). At the extreme, the differences may disappear, leading individuals to identical terminal situations, as in the case of purely deterministic trajectories. This indicates pseudo-deterministic trajectories. Finally, in chaotic trajectories, the slightest differences that students may experience during their studies and transition to work inevitably transform into growing differences between their situations over time, which ultimately leads them, without any further prediction being possible, to radically different arrival positions, at the opposite ends of the spectrum.

The identification of such trajectory dynamics obviously requires a precise measurement tool. AGIC calculator1 (Tchibozo, 2023) was designed for this purpose. Publicly accessible and requiring no specific technical prerequisites, AGIC enables everyone to enter into a model the initial socio-demographic (gender, age, social category, nationality, etc.) and educational (course of study, institution, etc.) characteristics, and the final quantitative occupational data (salary, number of hours worked, etc.) of cohorts of students in education-work transition, and to automatically identify the dynamics governing the trajectories of these cohorts.

The AGIC Calculator now enables educators, guidance counsellors, education policymakers, and researchers to determine whether a course of study has a deterministic, random, or chaotic effect on the trajectory of learners towards working life. On this basis, it is then possible to consider refining guidance counselling, by providing students with more precise information on the respective nature of the dynamics of the pathways they are considering, and the greater or lesser homogeneity of the outcomes of these pathways. For researchers, it becomes possible to better measure the relative place occupied by determinism (or each of the other dynamics) in each educational landscape. For policymakers, it becomes possible to better adjust actions aimed at correcting the effects of education systems on social inequalities and on the social trajectories of learners. In particular, the differences between the types of dynamics clearly suggest that interventions on pathways should be differentiated according to the dynamics that govern them.

Beyond this, the AGIC Calculator also paves the way for finer and more precise identification of the dynamics of social trajectories in a more general sense. In fact, it is not just the data on learners undergoing professional transitions that can be processed. AGIC can also be used to analyse the dynamics at work in any type of social trajectory, as long as this social trajectory can be represented by quantitative data on the initial and final situations of the individuals that take part in it. Thus, AGIC opens up new perspectives not only for analysing the dynamics of the education-to-work transition and social reproduction, but also for analysing the dynamics of social trajectories more generally.


1 The AGIC Calculator is based on a principle similar to that of the SSD Calculator, which can be used to characterise the dynamics of the allocation of budgetary resources to education policies, and more generally to public policies. The SSD Calculator can also be used to characterise the dynamics of any phenomenon that can be represented by a quantitative series containing at least half a dozen non-zero values. See Tchibozo (2024).


Tchibozo, G. (2004). The dynamics of school-to-work transition processes of university graduates: An analysis of French data. British Journal of Guidance and Counselling32(1), 93–108.

Tchibozo, G. (2023). AGIC calculator for the specification of the dynamics of school-to-work transition. https://gtsite.xyz/1/agic-calculator/

Tchibozo, G. (2024). A theory on specifying resource allocation dynamics in long-term multidimensional public policies. Stylit. https://gtsite.xyz/mqsef/dynamics/

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